Digitala Vetenskapliga Arkivet

Change search
Refine search result
1234567 1 - 50 of 6903
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Aaro, Gustav
    Linköping University, Department of Computer and Information Science.
    Smartphone Based Indoor Positioning Using Wi-Fi Round Trip Time and IMU Sensors2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    While GPS long has been an industry standard for localization of an entity or person anywhere in the world, it loses much of its accuracy and value when used indoors. To enable services such as indoor navigation, other methods must be used. A new standard of the Wi-Fi protocol, IEEE 802.11mc (Wi-Fi RTT), enables distance estimation between the transmitter and the receiver based on the Round-Trip Time (RTT) delay of the signal. Using these distance estimations and the known locations of the transmitting Access Points (APs), an estimation of the receiver’s location can be determined. In this thesis, a smartphone Wi-Fi RTT based Indoor Positioning System (IPS) is presented using an Unscented Kalman Filter (UKF). The UKF using only RTT based distance estimations as input, is established as a baseline implementation. Two extensions are then presented to improve the positioning performance; 1) a dead reckoning algorithm using smartphone sensors part of the Inertial Measurement Unit (IMU) as an additional input to the UKF, and 2) a method to detect and adjust distance measurements that have been made in Non-Line-of-Sight (NLoS) conditions. The implemented IPS is evaluated in an office environment in both favorable situations (plenty of Line-of-Sight conditions) and sub-optimal situations (dominant NLoS conditions). Using both extensions, meter level accuracy is achieved in both cases as well as a 90th percentile error of less than 2 meters.

    Download full text (pdf)
    fulltext
  • 2.
    Abarghouyi, Hadis
    et al.
    IUST, Sch Elect Engn, Tehran 1665973561, Iran.;MTNi Co, Tehran 1665973561, Iran..
    Razavizadeh, S. Mohammad
    IUST, Sch Elect Engn, Tehran 1684613114, Iran..
    Björnson, Emil
    Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
    QoE-Aware Beamforming Design for Massive MIMO Heterogeneous Networks2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 9, p. 8315-8323Article in journal (Refereed)
    Abstract [en]

    One of the main goals of the future wireless networks is improving the users' quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells' base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs' powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells' antennas in the network leads to a higher user satisfaction.

  • 3.
    Abari, Farzad Foroughi
    Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
    Optimization of Audio Processing algorithms (Reverb) on ARMv6 family of processors2008Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    Audio processing algorithms are increasingly used in cell phones and today’s customers are placing more demands on cell phones. Feature phones, once the advent of mobile phone technology, nowadays do more than just providing the user with MP3 play back or advanced audio effects. These features have become an integral part of medium as well as low-end phones. On the other hand, there is also an endeavor to include as improved quality as possible into products to compete in market and satisfy users’ needs. Tackling the above requirements has been partly satisfied by the advance in hardware design and manufacturing technology. However, as new hardware emerges into market the need for competence to write efficient software and exploit the new features thoroughly and effectively arises. Even though compilers are also keeping up with the new tide space for hand optimized code still exist. Wrapped in the above goal, an effort was made in this thesis to partly cover the competence requirement at Multimedia Section (part of Ericsson Mobile Platforms) to develope optimized code for new processors. Forging persistently ahead with new products, EMP has always incorporated the latest technology into its products among which ARMv6 family of processors has the main central processing role in a number of upcoming products. To fully exploit latest features provided by ARMv6, it was required to probe its new instruction set among which new media processing instructions are of outmost importance. In order to execute DSP-intensive algorithms (e.g. Audio Processing algorithms) efficiently, the implementation should be done in low-level code applying available instruction set. Meanwhile, ARMv6 comes with a number of new features in comparison with its predecessors. SIMD (Single Instruction Multiple Data) and VFP (Vector Floating Point) are the most prominent media processing improvements in ARMv6. Aligned with thesis goals and guidelines, Reverb algorithm which is among one of the most complicated audio features on a hand-held devices was probed. Consequently, its kernel parts were identified and implementation was done both in fixed-point and floating-point using the available resources on hardware. Besides execution time and amount of code memory for each part were measured and provided in tables and charts for comparison purposes. Conclusions were finally drawn based on developed code’s efficiency over ARM compiler’s as well as existing code already developed and tailored to ARMv5 processors. The main criteria for optimization was the execution time. Moreover, quantization effect due to limited precision fixed-point arithmetic was formulated and its effect on quality was elaborated. The outcomes, clearly indicate that hand optimization of kernel parts are superior to Compiler optimized alternative both from the point of code memory as well as execution time. The results also confirmed the presumption that hand optimized code using new instruction set can improve efficiency by an average 25%-50% depending on the algorithm structure and its interaction with other parts of audio effect. Despite its many draw backs, fixed-point implementation remains yet to be the dominant implementation for majority of DSP algorithms on low-power devices.

    Download full text (pdf)
    FULLTEXT01
  • 4.
    Abbas, Muhammad
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    On the Implementation of Integer and Non-Integer Sampling Rate Conversion2012Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The main focus in this thesis is on the aspects related to the implementation of integer and non-integer sampling rate conversion (SRC). SRC is used in many communication and signal processing applications where two signals or systems having different sampling rates need to be interconnected. There are two basic approaches to deal with this problem. The first is to convert the signal to analog and then re-sample it at the desired rate. In the second approach, digital signal processing techniques are utilized to compute values of the new samples from the existing ones. The former approach is hardly used since the latter one introduces less noise and distortion. However, the implementation complexity for the second approach varies for different types of conversion factors. In this work, the second approach for SRC is considered and its implementation details are explored. The conversion factor in general can be an integer, a ratio of two integers, or an irrational number. The SRC by an irrational numbers is impractical and is generally stated for the completeness. They are usually approximated by some rational factor.

    The performance of decimators and interpolators is mainly determined by the filters, which are there to suppress aliasing effects or removing unwanted images. There are many approaches for the implementation of decimation and interpolation filters, and cascaded integrator comb (CIC) filters are one of them. CIC filters are most commonly used in the case of integer sampling rate conversions and often preferred due to their simplicity, hardware efficiency, and relatively good anti-aliasing (anti-imaging) characteristics for the first (last) stage of a decimation (interpolation). The multiplierless nature, which generally yields to low power consumption, makes CIC filters well suited for performing conversion at higher rate. Since these filters operate at the maximum sampling frequency, therefore, are critical with respect to power consumption. It is therefore necessary to have an accurate and efficient ways and approaches that could be utilized to estimate the power consumption and the important factors that are contributing to it. Switching activity is one such factor. To have a high-level estimate of dynamic power consumption, switching activity equations in CIC filters are derived, which may then be used to have an estimate of the dynamic power consumption. The modeling of leakage power is also included, which is an important parameter to consider since the input sampling rate may differ several orders of magnitude. These power estimates at higher level can then be used as a feed-back while exploring multiple alternatives.

    Sampling rate conversion is a typical example where it is required to determine the values between existing samples. The computation of a value between existing samples can alternatively be regarded as delaying the underlying signal by a fractional sampling period. The fractional-delay filters are used in this context to provide a fractional-delay adjustable to any desired value and are therefore suitable for both integer and non-integer factors. The structure that is used in the efficient implementation of a fractional-delay filter is know as Farrow structure or its modifications. The main advantage of the Farrow structure lies in the fact that it consists of fixed finite-impulse response (FIR) filters and there is only one adjustable fractional-delay parameter, used to evaluate a polynomial with the filter outputs as coefficients. This characteristic of the Farrow structure makes it a very attractive structure for the implementation. In the considered fixed-point implementation of the Farrow structure, closed-form expressions for suitable word lengths are derived based on scaling and round-off noise. Since multipliers share major portion of the total power consumption, a matrix-vector multiple constant multiplication approach is proposed to improve the multiplierless implementation of FIR sub-filters.

    The implementation of the polynomial part of the Farrow structure is investigated by considering the computational complexity of different polynomial evaluation schemes. By considering the number of operations of different types, critical path, pipelining complexity, and latency after pipelining, high-level comparisons are obtained and used to short list the suitable candidates. Most of these evaluation schemes require the explicit computation of higher order power terms. In the parallel evaluation of powers, redundancy in computations is removed by exploiting any possible sharing at word level and also at bit level. As a part of this, since exponents are additive under multiplication, an ILP formulation for the minimum addition sequence problem is proposed.

    Download full text (pdf)
    On the Implementation of Integer and Non-Integer Sampling Rate Conversion
    Download (pdf)
    omslag
  • 5.
    Abbas, Muhammad
    et al.
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Gustafsson, Oscar
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    On the Fixed-Point Implementation of Fractional-Delay Filters Based on the Farrow Structure2013In: IEEE Transactions on Circuits and Systems Part 1: Regular Papers, ISSN 1549-8328, E-ISSN 1558-0806, Vol. 60, no 4, p. 926-937Article in journal (Refereed)
    Abstract [en]

    In this paper, the fixed-point implementation of adjustable fractional-delay filters using the Farrow structure is considered. Based on the observation that the sub-filters approximate differentiators, closed-form expressions for the L-2-norm scaling values at the outputs of each sub-filter as well as at the inputs of each delay multiplier are derived. The scaling values can then be used to derive suitable word lengths by also considering the round-off noise analysis and optimization. Different approaches are proposed to derive suitable word lengths including one based on integer linear programming, which always gives an optimal allocation. Finally, a new approach for multiplierless implementation of the sub-filters in the Farrow structure is suggested. This is shown to reduce register complexity and, for most word lengths, require less number of adders and subtracters when compared to existing approaches.

  • 6.
    Abbas, Muhammad
    et al.
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Gustafsson, Oscar
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Scaling of fractional delay filters based on the Farrow structure2009In: Proceedings of IEEE International Symposium on Circuits and Systems, 2009. ISCAS 2009, Piscataway: IEEE , 2009, p. 489-492Conference paper (Refereed)
    Abstract [en]

    In this work we consider scaling of fractional delay filters using the Farrow structure. Based on the observation that the subfilters approximate the Taylor expansion of a differentiator, we derive estimates of the L2-norm scaling values at the outputs of each subfilter as well as at the inputs of each delay multiplier. The scaling values can then be used to derive suitable wordlengths in a fixed-point implementation.

  • 7.
    Abbas, Taimoor
    et al.
    Lund Univ, Elect & Informat Technol Dept, S-22100 Lund, Sweden..
    Sjöberg, Katrin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Kåredal, Johan
    Lund Univ, Elect & Informat Technol Dept, S-22100 Lund, Sweden..
    Tufvesson, Fredrik
    Lund Univ, Elect & Informat Technol Dept, S-22100 Lund, Sweden..
    A Measurement Based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations2015In: International Journal of Antennas and Propagation, ISSN 1687-5869, E-ISSN 1687-5877, article id 190607Article in journal (Refereed)
    Abstract [en]

    The vehicle-to-vehicle (V2V) propagation channel has significant implications on the design and performance of novel communication protocols for vehicular ad hoc networks (VANETs). Extensive research efforts have been made to develop V2V channel models to be implemented in advanced VANET system simulators for performance evaluation. The impact of shadowing caused by other vehicles has, however, largely been neglected in most of the models, as well as in the system simulations. In this paper we present a shadow fading model targeting system simulations based on real measurements performed in urban and highway scenarios. The measurement data is separated into three categories, line-of-sight (LOS), obstructed line-of-sight (OLOS) by vehicles, and non-line-of-sight due to buildings, with the help of video information recorded during the measurements. It is observed that vehicles obstructing the LOS induce an additional average attenuation of about 10 dB in the received signal power. An approach to incorporate the LOS/OLOS model into existing VANET simulators is also provided. Finally, system level VANET simulation results are presented, showing the difference between the LOS/OLOS model and a channel model based on Nakagami-m fading.

  • 8.
    Abbaspour, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Electromyogram Signal Enhancement and Upper-Limb Myoelectric Pattern Recognition2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Losing a limb causes difficulties in our daily life. To regain the ability to live an independent life, artificial limbs have been developed. Hand prostheses belong to a group of artificial limbs that can be controlled by the user through the activity of the remnant muscles above the amputation. Electromyogram (EMG) is one of the sources that can be used for control methods for hand prostheses. Surface EMGs are powerful, non-invasive tools that provide information about neuromuscular activity of the subjected muscle, which has been essential to its use as a source of control for prosthetic limbs. However, the complexity of this signal introduces a big challenge to its applications. EMG pattern recognition to decode different limb movements is an important advancement regarding the control of powered prostheses. It has the potential to enable the control of powered prostheses using the generated EMG by muscular contractions as an input. However, its use has yet to be transitioned into wide clinical use. Different algorithms have been developed in state of the art to decode different movements; however, the challenge still lies in different stages of a successful hand gesture recognition and improvements in these areas could potentially increase the functionality of powered prostheses. This thesis firstly focuses on improving the EMG signal’s quality by proposing novel and advanced filtering techniques. Four efficient approaches (adaptive neuro-fuzzy inference system-wavelet, artificial neural network-wavelet, adaptive subtraction and automated independent component analysis-wavelet) are proposed to improve the filtering process of surface EMG signals and effectively eliminate ECG interferences. Then, the offline performance of different EMG-based recognition algorithms for classifying different hand movements are evaluated with the aim of obtaining new myoelectric control configurations that improves the recognition stage. Afterwards, to gain proper insight on the implementation of myoelectric pattern recognition, a wide range of myoelectric pattern recognition algorithms are investigated in real time. The experimental result on 15 healthy volunteers suggests that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) outperform other classifiers. The real-time investigation illustrates that in addition to the LDA and MLE, multilayer perceptron also outperforms the other algorithms when compared using classification accuracy and completion rate.

    Download full text (pdf)
    fulltext
  • 9.
    Abbaspour, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Evaluation of surface EMG-based recognition algorithms for decoding hand movementsManuscript (preprint) (Other academic)
  • 10.
    Abbaspour, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Proposing Combined Approaches to Remove ECG Artifacts from Surface EMG Signals2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Electromyography (EMG) is a tool routinely used for a variety of applications in a very large breadth of disciplines. However, this signal is inevitably contaminated by various artifacts originated from different sources. Electrical activity of heart muscles, electrocardiogram (ECG), is one of sources which affects the EMG signals due to the proximity of the collection sites to the heart and makes its analysis non-reliable. Different methods have been proposed to remove ECG artifacts from surface EMG signals; however, in spite of numerous attempts to eliminate or reduce this artifact, the problem of accurate and effective de-noising of EMG still remains a challenge. In this study common methods such as high pass filter (HPF), gating method, spike clipping, hybrid technique, template subtraction, independent component analysis (ICA), wavelet transform, wavelet-ICA, artificial neural network (ANN), and adaptive noise canceller (ANC) and adaptive neuro-fuzzy inference system (ANFIS) are used to remove ECG artifacts from surface EMG signals and their accuracy and effectiveness is investigated. HPF, gating method and spike clipping are fast; however they remove useful information from EMG signals. Hybrid technique and ANC are time consuming. Template subtraction requires predetermined QRS pattern. Using wavelet transform some artifacts remain in the original signal and part of the desired signal is removed. ICA requires multi-channel signals. Wavelet-ICA approach does not require multi-channel signals; however, it is user-dependent. ANN and ANFIS have good performance, but it is possible to improve their results by combining them with other techniques. For some applications of EMG signals such as rehabilitation, motion control and motion prediction, the quality of EMG signals is very important. Furthermore, the artifact removal methods need to be online and automatic. Hence, efficient methods such as ANN-wavelet, adaptive subtraction and automated wavelet-ICA are proposed to effectively eliminate ECG artifacts from surface EMG signals. To compare the results of the investigated methods and the proposed methods in this study, clean EMG signals from biceps and deltoid muscles and ECG artifacts from pectoralis major muscle are recorded from five healthy subjects to create 10 channels of contaminated EMG signals by adding the recorded ECG artifacts to the clean EMG signals. The artifact removal methods are also applied to the 10 channels of real contaminated EMG signals from pectoralis major muscle of the left side. Evaluation criteria such as signal to noise ratio, relative error, correlation coefficient, elapsed time and power spectrum density are used to evaluate the performance of the proposed methods. It is found that the performance of the proposed ANN-wavelet method is superior to the other methods with a signal to noise ratio, relative error and correlation coefficient of 15.53, 0.01 and 0.98 respectively.

    Download full text (pdf)
    fulltext
  • 11.
    Abbaspour, Sara
    et al.
    Amirkabir University of technology,Tehran, Iran.
    Fallah, Ali
    Amirkabir University of technology,Tehran, Iran.
    Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique2014In: Biomedical Physics and Engineering, ISSN 2251-7200, Vol. 4, no 1, p. 33-38Article in journal (Refereed)
    Abstract [en]

    Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result.

  • 12.
    Abbaspour, Sara
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    GholamHosseini, Hamid
    Auckland University of Technology, New Zealand.
    ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA2015In: Studies in Health Technology and Informatics, Volume 211, 2015, p. 91-97Conference paper (Refereed)
    Abstract [en]

    This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum.

  • 13.
    Abd Hamid, Fatimah Khairiah
    et al.
    Univ Teknol Mara, Coll Engn, Elect Engn Studies, Pasir Gudang Campus, Johor Baharu 81750, Malaysia..
    Hasan, Mohammed Nazibul
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Solid-State Electronics.
    Murty, Gantan Etika
    Imperial Coll London, Imperial Coll Business Sch, South Kensington Campus, London SW7 2AZ, England..
    Asri, Muhammad Izzudin Ahmad
    Flex Med, Senai Ind Area,Phase 3, Johor Baharu 81400, Malaysia..
    Saleh, Tanveer
    Int Islamic Univ Malaysia, Dept Mechatron Engn, Kuala Lumpur 53100, Malaysia..
    Ali, Mohamed Sultan Mohamed
    Qatar Univ, Coll Engn, Dept Elect Engn, Doha, Qatar.;Univ Teknol Malaysia, Fac Elect Engn, Johor Baharu 81310, Johor, Malaysia..
    Resistive strain sensors based on carbon black and multi-wall carbon nanotube composites2024In: Sensors and Actuators A-Physical, ISSN 0924-4247, E-ISSN 1873-3069, Vol. 366, article id 114960Article in journal (Refereed)
    Abstract [en]

    Strain sensors have garnered considerable interest, particularly in human motion and health monitoring, owing to their high stretchability and sensitivity. In this paper, resistive strain sensors comprising carbon black (CB)/ Ecoflex and multi-wall carbon nanotube (MWCNT)/Ecoflex with high sensitivity and large mechanical strain are presented. These sensors were developed using solution casting and dip-coating techniques. In addition, toluene and acetone were used to enhance the adhesion of CB and MWCNT to the Ecoflex substrate, thereby increasing electrical conductivity, sensitivity, and flexibility of the sensors while maintaining their high stretchability. Toluene-treated strain sensors exhibited the highest sensitivity for both CB/Ecoflex and MWCNT/Ecoflex strain sensors. As a result, the CB/Ecoflex sensor with toluene treatment achieved the highest gauge factor (GF) of -1131, which is 19 times higher than the original samples without surface treatment. Meanwhile, a GF of -106 is exhibited by the MWCNT/Ecoflex sensor, with toluene treatment improving sensitivity by a factor of 2 over untreated samples. These promising findings demonstrate the potential and prospects for flexible and wearable sensor applications.

  • 14.
    Abdalmoaty, Mohamed
    KTH, Reglerteknik.
    Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.

    The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.

    In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.

  • 15.
    Abdalmoaty, Mohamed
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.

    The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.

    In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.

    Download full text (pdf)
    fulltext
  • 16.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems2016In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3060-3065, article id 7798727Conference paper (Refereed)
    Abstract [en]

    This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

    Download full text (pdf)
    fulltext
  • 17.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem2018In: 18th IFAC Symposium on System Identification, 2018Conference paper (Refereed)
    Abstract [en]

    The estimation problem of stochastic Wiener-Hammerstein models is recognized to be challenging, mainly due to the analytical intractability of the likelihood function. In this contribution, we apply a computationally attractive prediction error method estimator to a real-data stochastic Wiener-Hammerstein benchmark problem. The estimator is defined using a deterministic predictor that is nonlinear in the input. The prediction error method results in tractable expressions, and Monte Carlo approximations are not necessary. This allows us to tackle several issues considered challenging from the perspective of the current mainstream approach. Under mild conditions, the estimator can be shown to be consistent and asymptotically normal. The results of the method applied to the benchmark data are presentedand discussed.

    Download full text (pdf)
    0028.pdf
  • 18.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 19.
    Abdalmoaty, Mohamed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    On Re-Weighting, Regularization Selection, and Transient in Nuclear Norm Based Identification2015In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 48, no 28, p. 92-97Article in journal (Refereed)
    Abstract [en]

    In this contribution, we consider the classical problem of estimating an Output Error model given a set of input-output measurements. First, we develop a regularization method based on the re-weighted nuclear norm heuristic. We show that the re-weighting improves the estimate in terms of better fit. Second, we suggest an implementation method that helps in eliminating the regularization parameters from the problem by introducing a constant based on a validation criterion. Finally, we develop a method for considering the effect of the transient when the initial conditions are unknown. A simple numerical example is used to demonstrate the proposed method in comparison to classical and another recent method based on the nuclear norm heuristic.

  • 20.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On Re-Weighting, Regularization Selection, and Transient in Nuclear Norm Based Identification2015Conference paper (Refereed)
    Abstract [en]

    In this contribution, we consider the classical problem of estimating an Output Error model given a set of input-output measurements. First, we develop a regularization method based on the re-weighted nuclear norm heuristic. We show that the re-weighting improves the estimate in terms of better fit. Second, we suggest an implementation method that helps in eliminating the regularization parameters from the problem by introducing a constant based on a validation criterion. Finally, we develop a method for considering the effect of the transient when the initial conditions are unknown. A simple numerical example is used to demonstrate the proposed method in comparison to classical and another recent method based on the nuclear norm heuristic.

    Download full text (pdf)
    fulltext
  • 21.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models2017In: The 20th IFAC World Congress, Elsevier, 2017, Vol. 50, p. 14058-14063Conference paper (Refereed)
    Abstract [en]

    Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.

    Download full text (pdf)
    fulltext
  • 22.
    Abdalmoaty, Mohamed
    et al.
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    Hjalmarsson, Håkan
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    Wahlberg, Bo
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    The Gaussian MLE versus the Optimally weighted LSE2020In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 37, no 6, p. 195-199Article in journal (Refereed)
    Abstract [en]

    In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.

  • 23.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Wahlberg, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    The Gaussian MLE versus the Optimally weighted LSE2020In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 37, no 6, p. 195-199Article in journal (Refereed)
    Abstract [en]

    In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.

    Download full text (pdf)
    fulltext
  • 24.
    Abdalmoaty, Mohamed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Noise reduction in Laguerre-domain discrete delay estimation2022In: 2022 IEEE 61st Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 6254-6259Conference paper (Refereed)
    Abstract [en]

    This paper introduces a stochastic framework for a recently proposed discrete-time delay estimation method in Laguerre-domain, i.e. with the delay block input and output signals being represented by the corresponding Laguerre series. A novel Laguerre-domain disturbance model allowing the involved signals to be square-summable sequences is devised. The relation to two commonly used time-domain disturbance models is clarified. Furthermore, by forming the input signal in a certain way, the signal shape of an additive output disturbance can be estimated and utilized for noise reduction. It is demonstrated that a significant improvement in the delay estimation error is achieved when the noise sequence is correlated. The noise reduction approach is applicable to other Laguerre-domain problems than pure delay estimation.

  • 25.
    Abdalmoaty, Mohamed R. H.
    et al.
    KTH, Reglerteknik.
    Rojas, Cristian R.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Identification of a Class of Nonlinear Dynamical Networks2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 868-873Article in journal (Refereed)
    Abstract [en]

    Identifcation of dynamic networks has attracted considerable interest recently. So far the main focus has been on linear time-invariant networks. Meanwhile, most real-life systems exhibit nonlinear behaviors; consider, for example, two stochastic linear time-invariant systems connected in series, each of which has a nonlinearity at its output. The estimation problem in this case is recognized to be challenging, due to the analytical intractability of both the likelihood function and the optimal one-step ahead predictors of the measured nodes. In this contribution, we introduce a relatively simple prediction error method that may be used for the estimation of nonlinear dynamical networks. The estimator is defined using a deterministic predictor that is nonlinear in the known signals. The estimation problem can be defined using closed-form analytical expressions in several non-trivial cases, and Monte Carlo approximations are not necessarily required. We show, that this is the case for some block-oriented networks with no feedback loops and where all the nonlinear modules are polynomials. Consequently, the proposed method can be applied in situations considered challenging by current approaches. The performance of the estimation method is illustrated on a numerical simulation example.

  • 26.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems2016In: 2016 IEEE 55th Conference on Decision and Control (CDC), IEEE, 2016, p. 3060-3065Conference paper (Refereed)
    Abstract [en]

    This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

  • 27.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 784-789Article in journal (Refereed)
    Abstract [en]

    The estimation problem of stochastic Wiener-Hammerstein models is recognized to be challenging, mainly due to the analytical intractability of the likelihood function. In this contribution, we apply a computationally attractive prediction error method estimator to a real-data stochastic Wiener-Hammerstein benchmark problem. The estimator is defined using a deterministic predictor that is nonlinear in the input. The prediction error method results in tractable expressions, and Monte Carlo approximations are not necessary. This allows us to tackle several issues considered challenging from the perspective of the current mainstream approach. Under mild conditions, the estimator can be shown to be consistent and asymptotically normal. The results of the method applied to the benchmark data are presented and discussed.

  • 28.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018In: 2018 IEEE Conference on Decision and Control (CDC), IEEE, 2018, p. 3842-3847Conference paper (Refereed)
    Abstract [en]

    We consider a parameter estimation problem in a general class of stochastic multiple-inputs multiple-outputs Wiener models, where the likelihood function is, in general, analytically intractable. When the output signal is a scalar independent stochastic process, the likelihood function of the parameters is given by a product of scalar integrals. In this case, numerical integration may be efficiently used to approximately solve the maximum likelihood problem. Otherwise, the likelihood function is given by a challenging multidimensional integral. In this contribution, we argue that by ignoring the temporal and spatial dependence of the stochastic disturbances, a computationally attractive estimator based on a suboptimal predictor can be constructed by evaluating scalar integrals regardless of the number of outputs. Under some conditions, the convergence of the resulting estimators can be established and consistency is achieved under certain identifiability hypothesis. We highlight the relationship between the resulting estimators and a recently proposed prediction error method estimator. We also remark that the method can be used for a wider class of stochastic nonlinear models. The performance of the method is demonstrated by a numerical simulation example using a 2-inputs 2-outputs model with 9 parameters.

  • 29.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models2017In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 50, no 1, p. 14058-14063Article in journal (Refereed)
    Abstract [en]

    Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.

  • 30.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Identication of a Class of Nonlinear Dynamical Networks2018Conference paper (Refereed)
    Abstract [en]

    Identifcation of dynamic networks has attracted considerable interest recently. So far the main focus has been on linear time-invariant networks. Meanwhile, most real-life systems exhibit nonlinear behaviors; consider, for example, two stochastic linear time-invariant systems connected in series, each of which has a nonlinearity at its output. The estimation problem in this case is recognized to be challenging, due to the analytical intractability of both the likelihood function and the optimal one-step ahead predictors of the measured nodes. In this contribution, we introduce a relatively simple prediction error method that may be used for the estimation of nonlinear dynamical networks. The estimator is defined using a deterministic predictor that is nonlinear in the known signals. The estimation problem can be defined using closed-form analytical expressions in several non-trivial cases, and Monte Carlo approximations are not necessarily required. We show, that this is the case for some block-oriented networks with no feedback loops and where all the nonlinear modules are polynomials. Consequently, the proposed method can be applied in situations considered challenging by current approaches. The performance of the estimation method is illustrated on a numerical simulation example.

    Download full text (pdf)
    0131.pdf
  • 31.
    Abd-Elmagid, Mohamed A.
    et al.
    Virginia Tech, VA 24061 USA.
    Dhillon, Harpreet S.
    Virginia Tech, VA 24061 USA.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    A Reinforcement Learning Framework for Optimizing Age of Information in RF-Powered Communication Systems2020In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, no 8, p. 4747-4760Article in journal (Refereed)
    Abstract [en]

    In this paper, we study a real-time monitoring system in which multiple source nodes are responsible for sending update packets to a common destination node in order to maintain the freshness of information at the destination. Since it may not always be feasible to replace or recharge batteries in all source nodes, we consider that the nodes are powered through wireless energy transfer (WET) by the destination. For this system setup, we investigate the optimal online sampling policy (referred to as the age-optimal policy) that jointly optimizes WET and scheduling of update packet transmissions with the objective of minimizing the long-term average weighted sum of Age of Information (AoI) values for different physical processes (observed by the source nodes) at the destination node, referred to as the sum-AoI. To solve this optimization problem, we first model this setup as an average cost Markov decision process (MDP) with finite state and action spaces. Due to the extreme curse of dimensionality in the state space of the formulated MDP, classical reinforcement learning algorithms are no longer applicable to our problem even for reasonable-scale settings. Motivated by this, we propose a deep reinforcement learning (DRL) algorithm that can learn the age-optimal policy in a computationally-efficient manner. We further characterize the structural properties of the age-optimal policy analytically, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. We extend our analysis to characterize the structural properties of the policy that maximizes average throughput for our system setup, referred to as the throughput-optimal policy. Afterwards, we analytically demonstrate that the structures of the age-optimal and throughput-optimal policies are different. We also numerically demonstrate these structures as well as the impact of system design parameters on the optimal achievable average weighted sum-AoI.

    Download full text (pdf)
    fulltext
  • 32.
    Abd-Elrady, Emad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Harmonic signal modeling based on the Wiener model structure2002Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The estimation of frequencies and corresponding harmonic overtones is a problem of great importance in many situations. Applications can, for example, be found in supervision of electrical power transmission lines, in seismology and in acoustics. Generally, a periodic function with an unknown fundamental frequency in cascade with a parameterized and unknown nonlinear function can be used as a signal model for an arbitrary periodic signal. The main objective of the proposed modeling technique is to estimate the fundamental frequency of the periodic function in addition to the parameters of the nonlinear function.

    The thesis is divided into four parts. In the first part, a general introduction to the harmonic signal modeling problem and different approaches to solve the problem are given. Also, an outline of the thesis and future research topics are introduced.

    In the second part, a previously suggested recursive prediction error method (RPEM) for harmonic signal modeling is studied by numerical examples to explore the ability of the algorithm to converge to the true parameter vector. Also, the algorithm is modified to increase its ability to track the fundamental frequency variations.

    A modified algorithm is introduced in the third part to give the algorithm of the second part a more stable performance. The modifications in the RPEM are obtained by introducing an interval in the nonlinear block with fixed static gain. The modifications that result in the convergence analysis are, however, substantial and allows a complete treatment of the local convergence properties of the algorithm. Moreover, the Cramér–Rao bound (CRB) is derived for the modified algorithm and numerical simulations indicate that the method gives good results especially for moderate signal to noise ratios (SNR).

    In the fourth part, the idea is to give the algorithm of the third part the ability to estimate the driving frequency and the parameters of the nonlinear output function parameterized also in a number of adaptively estimated grid points. Allowing the algorithm to automatically adapt the grid points as well as the parameters of the nonlinear block, reduces the modeling errors and gives the algorithm more freedom to choose the suitable grid points. Numerical simulations indicate that the algorithm converges to the true parameter vector and gives better performance than the fixed grid point technique. Also, the CRB is derived for the adaptive grid point technique.

    Download full text (ps)
    fulltext
  • 33.
    Abd-Elrady, Emad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nonlinear Approaches to Periodic Signal Modeling2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Periodic signal modeling plays an important role in different fields. The unifying theme of this thesis is using nonlinear techniques to model periodic signals. The suggested techniques utilize the user pre-knowledge about the signal waveform. This gives these techniques an advantage as compared to others that do not consider such priors.

    The technique of Part I relies on the fact that a sine wave that is passed through a static nonlinear function produces a harmonic spectrum of overtones. Consequently, the estimated signal model can be parameterized as a known periodic function (with unknown frequency) in cascade with an unknown static nonlinearity. The unknown frequency and the parameters of the static nonlinearity are estimated simultaneously using the recursive prediction error method (RPEM). A treatment of the local convergence properties of the RPEM is provided. Also, an adaptive grid point algorithm is introduced to estimate the unknown frequency and the parameters of the static nonlinearity in a number of adaptively estimated grid points. This gives the RPEM more freedom to select the grid points and hence reduces modeling errors.

    Limit cycle oscillations problem are encountered in many applications. Therefore, mathematical modeling of limit cycles becomes an essential topic that helps to better understand and/or to avoid limit cycle oscillations in different fields. In Part II, a second-order nonlinear ODE is used to model the periodic signal as a limit cycle oscillation. The right hand side of the ODE model is parameterized using a polynomial function in the states, and then discretized to allow for the implementation of different identification algorithms. Hence, it is possible to obtain highly accurate models by only estimating a few parameters.

    In Part III, different user aspects for the two nonlinear approaches of the thesis are discussed. Finally, topics for future research are presented.

    Download full text (pdf)
    FULLTEXT01
  • 34.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal analysis using orbits of nonlinear ODEs based on the Markov estimate2004Conference paper (Refereed)
  • 35.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal modeling based on Liénard's equation2004In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 49, no 10, p. 1773-1778Article in journal (Refereed)
  • 36.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal modeling based on Liénard's equation2003Report (Other academic)
    Download full text (pdf)
    fulltext
  • 37. Abdu, Tedros Salih
    et al.
    Kisseleff, Steven
    Lagunas, Eva
    Chatzinotas, Symeon
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg, Luxembourg.
    Demand and Interference Aware Adaptive Resource Management for High Throughput GEO Satellite Systems2022In: IEEE Open Journal of the Communications Society, E-ISSN 2644-125X, Vol. 3, p. 759-775Article in journal (Refereed)
    Abstract [en]

    The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS) systems. Accordingly, future satellites are expected to employ advanced resource/interference management techniques to achieve high system spectrum efficiency and low power consumption while ensuring user demand satisfaction. This paper proposes a novel demand and interference aware adaptive resource management for geostationary (GEO) VHTS systems. For this, we formulate a multi-objective optimization problem to minimize the total transmit power consumption and system bandwidth usage while matching the offered capacity with the demand per beam. In this context, we consider resource management for a system with full-precoding, i.e., all beams are precoded; without precoding, i.e., no precoding is applied to any beam; and with partial precoding, i.e., only some beams are precoded. The nature of the problem is non-convex and we solve it by jointly using the Dinkelbach and Successive Convex Approximation (SCA) methods. The simulation results show that the proposed method outperforms the benchmark schemes. Specifically, we show that the proposed method requires low resource consumption, low computational time, and simultaneously achieves a high demand satisfaction.

  • 38. Abdu, Tedros Salih
    et al.
    Kisseleff, Steven
    Lagunas, Eva
    Grotz, Joel
    Chatzinotas, Symeon
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Luxembourg.
    Demand-Aware Onboard Payload Processor Management for High Throughput NGSO Satellite Systems2023In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 00189251, p. 1-18Article in journal (Refereed)
    Abstract [en]

    High-Throughput Satellite (HTS) systems with digital payload technology have been identified as a key enabler to support 5G/6G high-data connectivity with wider coverage area. The satellite community has extensively explored resource allocation methods to achieve this target. Typically, these methods do not consider the intrinsic architecture of the flexible satellite digital payload, which consists of multiple processors responsible for receiving, processing, and transmitting the signals. This paper presents a demand-aware onboard processor management scheme for broadband Non-Geostationary (NGSO) satellites. In this context, we formulate an optimization problem to minimize the number of active on-board processors while meeting the system constraints and user requirements. As the problem is non-convex, we solve it in two steps. First, we transform the problem into demand-driven bandwidth allocation while fixing the number of processors. Second, using the bandwidth allocation solution, we determine the required number of processors with two methods: 1) sequential optimization with the Branch & Bound method and 2) Bin Packing with Next Fit, First Fit, and Best Fit methods. Finally, we demonstrate the proposed methods with extensive numerical results. It is shown that the Branch & Bound, Best Fit, and First Fit methods manage the processors better than the Next Fit method. Furthermore, Branch & Bound requires fewer processors than the above methods.

  • 39. Abdullah, Zaid
    et al.
    Kisseleff, Steven
    Alves Martins, Wallace
    Chen, Gaojie
    Sanguinetti, Luca
    Ntontin, Konstantinos
    Papazafeiropoulos, Anastasios
    Chatzinotas, Symeon
    Ottersten, Björn
    University of Luxembourg, Luxembourg.
    Cooperative Hybrid Networks with Active Relays and RISs for B5G: Applications, Challenges, and Research Directions2022In: IEEE Wireless Communications, ISSN 15361284, p. 1-7Article in journal (Refereed)
    Abstract [en]

    Among the recent advances and innovations in wireless technologies, reconfigurable intelligent surfaces (RISs) have received much attention and are envisioned to be one of the enabling technologies for beyond 5G (B5G) networks. On the other hand, active (or classical) cooperative relays have played a key role in providing reliable and power-efficient communications in previous wireless generations. In this article, we focus on hybrid network architectures that amalgamate both active relays and RISs. The operation concept and protocols of each technology are first discussed. Subsequently, we present multiple use cases of cooperative hybrid networks where both active relays and RISs can coexist harmoniously for enhanced rate performance. Furthermore, a case study is provided which demonstrates the achievable rate performance of a communication network assisted by either an active relay, an RIS, or both, and with different relaying protocols. Finally, we provide the reader with the challenges and key research directions in this area.

  • 40.
    Abdullah, Zaid
    et al.
    Interdisciplinary Centre for Security, Reliability and Trust (Sn T), University of Luxembourg, L-1855, Luxembourg..
    Papazafeiropoulos, Anastasios
    Communications and Intelligent Systems Research Group, University of Hertfordshire, Hatfield AL10 9AB, U.K., and also with the SnT, University of Luxembourg, Luxembourg..
    Kisseleff, Steven
    Interdisciplinary Centre for Security, Reliability and Trust (Sn T), University of Luxembourg, L-1855, Luxembourg..
    Chatzinotas, Symeon
    Interdisciplinary Centre for Security, Reliability and Trust (Sn T), University of Luxembourg, L-1855, Luxembourg..
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust (Sn T), University of Luxembourg, L-1855, Luxembourg..
    Impact of Phase-Noise and Spatial Correlation on Double-RIS-Assisted Multiuser MISO Networks2022In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, p. 1-1Article in journal (Refereed)
  • 41.
    Abedan Kondori, Farid
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being.

    The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis.

    Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

    Download full text (pdf)
    fulltext
  • 42.
    Abedan Kondori, Farid
    et al.
    Department of Applied Physics and Electronics, Umeå University, Umea, Sweden.
    Yousefi, Shahrouz
    Department of Applied Physics and Electronics, Umeå University, Umea, Sweden.
    Smart Baggage in Aviation2011In: Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, 2011Conference paper (Refereed)
    Abstract [en]

    Nowadays, the Internet has dramatically changed the way people take the normal course of actions. By the recent growth of the Internet, connecting different objects to users through mobile phones and computers is no longer a dream. Aviation industry is one of the areas which have a strong potential to benefit from the Internet of Things. Among many problems related to air travel, delayed and lost luggage are the most common and irritating. Therefore, this paper suggests anew baggage control system, where users can simply track their baggage at the airport to avoid losing them. Attaching a particular pattern on the bag, which can be detected and localized from long distance by an ordinary camera, users are able to track their baggage. The proposed system is much cheaper than previous implementations and does not require sophisticated equipment.

  • 43.
    Abedan Kondori, Farid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Yousefi, Shahrouz
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Kouma, Jean-Paul
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Liu, Li
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Li, Haibo
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Direct hand pose estimation for immersive gestural interaction2015In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 66, p. 91-99Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel approach for performing intuitive gesture based interaction using depth data acquired by Kinect. The main challenge to enable immersive gestural interaction is dynamic gesture recognition. This problem can be formulated as a combination of two tasks; gesture recognition and gesture pose estimation. Incorporation of fast and robust pose estimation method would lessen the burden to a great extent. In this paper we propose a direct method for real-time hand pose estimation. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Extensive experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation On two different setups; desktop computing, and mobile platform. This reveals the system capability to accommodate different interaction procedures. In addition, a user study is conducted to evaluate learnability, user experience and interaction quality in 3D gestural interaction in comparison to 2D touchscreen interaction.

  • 44. Abedan Kondori, Farid
    et al.
    Yousefi, Shahrouz
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Li, Haibo
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Direct Head Pose Estimation Using Kinect-type Sensors2014In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911XArticle in journal (Refereed)
  • 45.
    Abedan Kondori, Farid
    et al.
    Umeå universitet.
    Yousefi, Shahrouz
    KTH Royal Institute of Technology.
    Li, Haibo
    KTH Royal Institute of Technology.
    Direct three-dimensional head pose estimation from Kinect-type sensors2014In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 50, no 4, p. 268-270Article in journal (Refereed)
    Abstract [en]

    A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(xyt), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(xyt). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

  • 46.
    Abedan Kondori, Farid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Yousefi, Shahrouz
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Li, Haibo
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Direct three-dimensional head pose estimation from Kinect-type sensors2014In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 50, no 4, p. 268-270Article in journal (Refereed)
    Abstract [en]

    A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(xyt), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(xyt). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

  • 47.
    Abedan Kondori, Farid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Yousefi, Shahrouz
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Liu, Li
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Li, Haibo
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Head operated electric wheelchair2014In: IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI 2014), IEEE , 2014, p. 53-56Conference paper (Refereed)
    Abstract [en]

    Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.

  • 48. Abedan Kondori, Farid
    et al.
    Yousefi, Shahrouz
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Liu, Li
    Li, Haibo
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID. Nanjing University of Posts and Telecommunications, Nanjing, China .
    Head Operated Electric Wheelchair2014In: Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2014, p. 53-56Conference paper (Refereed)
    Abstract [en]

    Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.

  • 49.
    Abelsson, Sara
    Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
    Propagation Measurements at 3.5 GHz for WiMAX2007Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Propagation measurements at the frequency 3.5 GHz for the WiMAX technology have been conducted. The purpose of these measurements is that a coverage analysis should be accomplished. The mathematical software package MATLAB has been used to analyze the collected data from the measurement campaign. Path loss models have also been used and a comparison between these models and the collected data has been performed. An analysis prediction tool from an application called WRAP has also been used in the comparison with the collected data. In this thesis, diff

    Download full text (pdf)
    FULLTEXT01
  • 50.
    Abou Raas, Mhd Jihad
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences.
    Wall Compensation Algorithms for M-sequence UWB Radar2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A technique for wall compensation in the ultra-wideband (UWB) through-wall imaging radar is presented. The UWB system can be utilize in high precision measurements, but due to phase distortion and amplitude attenuation caused by the wall the precision is limited, the target is displaced, and the image is defocused. 

    In order to mitigate the wall effects, two methods are applied in this project. First, the unknown wall transfer function is estimated using real data measurements to design the inverse filter. Secondly, FIR Wiener filter is designed to improve the received m-sequence. After all, each method is tested using three parameters, the signal to noise ratio (SNR), the signal to clutter ratio (SCR), and the relative position error (RPE). 

    The inverse filter can eliminate the wall effects very well; it could correct not only the position of the target but also the image defocus. The new method can give improve the image quality and that can extend the use of UWB radar in many applications. 

    Download full text (pdf)
    fulltext
1234567 1 - 50 of 6903
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf