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matching pursuit algorithm for enhancing EEG signal quality and increasing the accuracy and efficiency of emotion recognition

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BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK 2020年第4期65卷 393-404页

作者： Momennezhad, Ali Sahand Univ Technol Tabriz Sahand 199651335 Tabriz Iran

In this paper, we suggest an efficient, accurate and user-friendly brain-computer interface (BCI) system for recognizing and distinguishing different emotion states. For this, we used a multimodal dataset entitled "MAHOB-HCI" which can be freely reached through an email request. This research is based on electroencephalogram (EEG) signals carrying emotions and excludes other physiological features, as it finds EEG signals more reliable to extract deep and true emotions compared to other physiological features. EEG signals comprise low information and signal-to-noise ratios (SNRs);so it is a huge challenge for proposing a robust and dependable emotion recognition algorithm. For this, we utilized a new method, based on the matching pursuit (MP) algorithm, to resolve this imperfection. We applied the MP algorithm for increasing the quality and SNRs of the original signals. In order to have a signal of high quality, we created a new dictionary including 5-scale Gabor atoms with 5000 atoms. For feature extraction, we used a 9-scale wavelet algorithm. A 32-electrode configuration was used for signal collection, but we used just eight electrodes out of that;therefore, our method is highly user-friendly and convenient for users. In order to evaluate the results, we compared our algorithm with other similar works. In average accuracy, the suggested algorithm is superior to the same algorithm without applying MP by 2.8% and in terms of f-score by 0.03. In comparison with corresponding works, the accuracy and f-score of the proposed algorithm are better by 10.15% and 0.1, respectively. So as it is seen, our method has improved past works in terms of accuracy, f-score and user-friendliness despite using just eight electrodes.

关键词： ANOVA BINARY-SVM coherence EEG emotion recognition matching pursuit algorithm wavelet coefficients

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Investigating body motion patterns in patients with Parkinson's disease using matching pursuit algorithm

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MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 2004年第1期42卷 30-36页

作者： Sekine, M Akay, M Tamura, T Higashi, Y Fujimoto, T Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Natl Inst Longev Sci Dept Gerontechnol Aichi Japan Fujimoto Hayasuzu Hosp Miyazaki Japan

Several recent studies have quantified abnormalities in Parkinsonian gait. However, few studies have attempted to quantify the regularity of body motion during walking in patients with Parkinson's disease. The aim of the paper was to characterise body motion patterns in healthy, elderly subjects and patients with Parkinson's disease during walking. Body motion was recorded during walking for 16 patients with Parkinson's disease and ten healthy, elderly subjects using a tri-axial accelerometer device. To characterise the body motion patterns, time-frequency patterns of the body acceleration signal were estimated using a matching pursuit algorithm. Data from the study showed that the healthy, elderly subjects and patients with Parkinson's disease had different time-frequency patterns. The time-frequency patterns were classified into four distinct patterns based on their time durations: vertical (< 0.15 s), circular (0.15-0.5 s), short horizontal (0.5-2.0 s) and long horizontal (> 2.0s). The data showed that the energy of the long horizontal patterns, representing long-term smooth and regular (rhythmic) activities, significantly decreased, but the energy of the circular patterns, representing irregular activities, increased in the patients with mild Parkinson's disease, compared with those of the healthy, elderly subjects (p < 0.01). Futhermore, these features were seen more clearly in the body motions of severe case patients than is that of mild case patients. It was concluded that these differences are probably due to a lack of ability to control normal and smooth movement is Parkinson's disease.

关键词： Parkinson's disease body motion acceleration signal gait time-frequency patterns matching pursuit algorithm

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The matching pursuit algorithm revisited: A variant for big data and new stopping rules

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SIGNAL PROCESSING 2019年 155卷 170-181页

作者： Li, Fangyao Triggs, Christopher M. Dumitrescu, Bogdan Giurcaneanu, Ciprian Doru Univ Auckland Dept Stat Private Bag 92019 Auckland 1142 New Zealand Univ Politehn Bucuresti 313 Spl Independentei Bucharest 060042 Romania

The matching pursuit algorithm (MPA) is used in many applications for selecting the best predictors for a vector of measurements of size n from a dictionary that contains pn atoms, where usually n <= p(n). A major unsolved problem is to determine the optimal stopping rule. In this work, we investigate various stopping rules which are modifications of the information theoretic (IT) criteria derived for Gaussian linear regression. Because all of them involve the degrees of freedom (df) given by the trace of the hat matrix, we provide some theoretical results concerning this matrix. We also propose novel stopping rules. An important contribution of this paper is a method for computing the df efficiently when big data (n >> p(n)) are processed. The significance of the auxiliary variables appearing in MPA for big data is clarified via a theoretical analysis. The superiority of the new stopping rules in comparison with the traditional approaches is demonstrated in simulations involving big data (n >> p(n)) or overcomplete dictionaries (n < p(n)) and in experiments with air pollution data. (C) 2018 Elsevier B.V. All rights reserved.

关键词： matching pursuit algorithm Hat matrix Big data Information theoretic criteria Air pollution data

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Damage detection of anchored region on the messenger cable based on matching pursuit algorithm

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 130卷 221-247页

作者： Hong, Xiaobin Zhou, Jianxi He, Yongkui South China Univ Technol Sch Mech & Automot Engn Guangzhou 510640 Guangdong Peoples R China

The messenger cable is the main bearing part of the electrified railway catenary. Damage is easily generated in the anchored region and difficult to detect, and will cause a major accident if left unchecked. At present, the damage detection method is mainly for the bare part of the strand, but rarely about the covered region. Therefore, this paper proposes an ultrasonic guided wave detection method, which is based on matching pursuit algorithm and the developed chain detection device to monitor the region covered by the mid-anchor clamp. Firstly, according to the propagation characteristics of the ultrasonic guided wave in the stranded structure, the pulse echo detection method was adopted and the arrangement of piezoceramic transducers was determined. Secondly, the mechanism between the guided wave and the damage was analyzed by the matching pursuit algorithm in finite element simulation. Then, a chain detection device was designed based on the detection method and simulation results. Finally, a series of experiments were carried out under different temperature conditions and different tensile stress conditions. The experimental results show that the damage depth over 2.5 mm on single-wire can be detected by the proposed method, which satisfies the detection requirements of electrified railway messenger cable. This research provides an effective method for detection the catenary damage of electrified railway. (C) 2019 Published by Elsevier Ltd.

关键词： Messenger cable Anchored region Damage detection Ultrasonic guided wave matching pursuit algorithm Chain detection device

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Two-Stage Fast matching pursuit algorithm for Multi-Target Localization

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IEEE ACCESS 2023年 11卷 66318-66326页

作者： Dong, Ningfei Zhang, Lei Zhou, Haosu Li, Xiaolin Wu, Shie Liu, Xia Yantai Univ Sch Phys & Elect Informat Yantai 264005 Peoples R China Yantai Acad Agr Sci Yantai 265500 Peoples R China Shanghai Spaceflight Inst TT&C & Telecommun Shanghai 201109 Peoples R China

For large-scale high-dimensional positioning scenes, the massive number of grid points brings challenges to the multi-target positioning algorithms based on compressed sensing. To cope with the challenges, a fast multi-target localization method based on direction of arrival is proposed. A compressed sensing model is constructed for multi-target localization based on the DOA sequence measured by positioning nodes. Then, a two-stage fast matching pursuit algorithm is presented for sparse reconstruction, which consists of preliminary estimation and supports rectification. A process similar to orthogonal matching pursuit algorithm is adopted to get preliminary estimate result, but no nonlinear operations is employed for complexity reduction. Then another iterative process is carried out to rectify the chosen supports in preliminary result sequentially. Simulation results verify the effectiveness and accuracy of the proposed method for multi-target localization.

关键词： Direction of arrival matching pursuit algorithm multi-target localization sparse recovery

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Damage characterization based on nonlinear guided wave simulation and chirplet matching pursuit algorithm 12

Damage characterization based on nonlinear guided wave simul...

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SPIE Conference on Health Monitoring of Structural and Biological Systems XII

作者： Zhang, Hui Cesnik, Carlos E. S. Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

ISBN: (数字)9781510616974

ISBN: (纸本)9781510616974

The paper presents a damage characterization framework based on a simulation library and matching pursuit algorithm to estimate damage features in typical aerospace structures. The large damage database is generated by numeric simulation. The recent development of the University of Michigan's Local Interaction Simulation Approach (UM/LISA) is an ideal tool for generating such a damage database in a very efficient manner. It includes capability for piezoelectric coupled field simulation, non-reflective boundary techniques, and contact penalty method for nonlinear guided wave simulation, and can execute on multiple-GPU platform for fast computation. The selected damage identification problem in the paper is modeled as contact interface and simulated in UM/LISA using the contact penalty method. The process first populates a library of possible damage signals using UM/LISA by varying damage parameters, such as crack length, depth and orientation. The matching pursuit decomposes the damage difference signals into atoms and the atom parameters are used as signal features. Then the algorithm evaluates a matching merit metric and its special distribution provides parametric regions of damage presence. A representative model of fatigue cracks on aluminum plate considering various crack scenarios is investigated to test the effectiveness of the algorithm. The relation between the crack features and signal features provides better understanding of the nonlinear interactions between the guided waves and fatigue cracks. The matching quality plots demonstrate that the framework can provide good estimation of the crack parameters.

关键词： Structural health monitoring damage detection damage characterization matching pursuit algorithm UM/LISA non-reflective boundary method multiple GPU parallelization

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A comparison of two extensions of the matching pursuit algorithm for the harmonic decomposition of sounds

A comparison of two extensions of the matching pursuit algor...

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Workshop on Applications of Signal Processing to Audio and Acoustics

作者： Krstulovic, S Gribonval, R Leveau, P Daudet, L Inst Rech Informat & Syst Aleatoires F-35042 Rennes France

ISBN: (纸本)0780391543

In the framework of audio signal analysis, it is desired to obtain sparse representations that are able to reflect the harmonic structures, e.g., issued from musical instruments. In this paper, we compare two approaches which introduce sonic explicit models of harmonic features into the matching pursuit analysis framework. The first approach is the Harmonic matching pursuit (HMP), where the harmonic structures are modeled by sets of harmonically related Gabor atoms which Lire directly optimized in the analysis loop. The second approach, called Meta-Molecular matching pursuit (M3P), is based on the a posteriori agglomeration of elementary features coming from it Short Time Fourier Transform. We discuss file pros and cons of each method through experiments involving different audio signals, and conclude oil possible approaches for combining the two methods.

关键词： Fourier transforms acoustic signal processing audio signal processing harmonics iterative methods time-frequency analysis Gabor atoms a posteriori agglomeration audio signal analysis harmonic decomposition harmonic structures matching pursuit algorithm m

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DDoS Attack Detection Using matching pursuit algorithm 24

DDoS Attack Detection Using Matching Pursuit Algorithm

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24th Signal Processing and Communication Application Conference (SIU)

作者： Erhan, Derya Anarim, Emin Kurt, Gunes Karabulut Bogazici Univ Elekt & Elekt Muhendisligi Bolumu Istanbul Turkey Istanbul Tech Univ Elekt & Elekt Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781509016792

Distributed denial of service attacks pose an immense threat to the internet. In this work TCP SYN flood attacks are detected using matching pursuit algorithm. Dictionaries are generated using K-SVD algorithm from normal and attack traffic of training data. Using these dictionaries and applying matching pursuit algorithm detection of attacks are performed pursing resulting residuals of matching pursuit operation.

关键词： DDoS intrusion detection denial of service signal processing matching pursuit algorithm

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A New Compressed Sensing-Based matching pursuit algorithm for Image Reconstruction

A New Compressed Sensing-Based Matching Pursuit Algorithm fo...

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5th International Congress on Image and Signal Processing (CISP)

作者： Fang, Hong Yang, Hairong Shanghai Second Polytech Univ Sch Sci Shanghai 201209 Peoples R China

ISBN: (纸本)9781467309646;9781467309653

Compressed Sensing (CS), a popular technique which seeks to capture a discrete signal with a small number of linear measurements, could be used to compress a signal during the process of sampling. As an iterative greedy reconstruction algorithm for practical CS, sparsity adaptive matching pursuit (SAMP) takes advantage of the capability of signal reconstruction without prior information of the sparsity in the process of resuming the original high-dimension-data from low-dimension measurement. This paper presents a backward and adaptive matching pursuit reconstruction algorithm with fixed step sizes to avoid the overestimation phenomena of SAMP by using a standard regularized approach. Firstly, a fixed and biggish step size is set to make sure the size of support set of the signal to be reconstructed increasing stably. The energy difference between adjacent reconstructed signals is then taken as the halting condition of iteration. A standard regularized approach is employed to post-dispose the final iteration results, which backward eliminates superfluous atoms to acquire exact reconstruction. Experimental results show that such an improvement of SAMP is feasible in technology and effective in acquiring quick and exact reconstruction with sufficient measurement.

关键词： Image reconstruction matching pursuit algorithm compressive sensing sparse representation

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ON THE NUMBER OF ITERATIONS FOR THE matching pursuit algorithm 25

ON THE NUMBER OF ITERATIONS FOR THE MATCHING PURSUIT ALGORIT...

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25th European Signal Processing Conference (EUSIPCO)

ISBN: (纸本)9780992862671

We address the problem of selecting, from a given dictionary, a subset of predictors whose linear combination provides the best description for the vector of measurements. To this end, we apply the well-known matching pursuit algorithm (MPA). Even if there are theoretical results on the performance of MPA, there is no widely accepted rule for stopping the algorithm. In this work, we focus on stopping rules based on information theoretic criteria (ITC). The key point is to evaluate the degrees of freedom (df) for the model produced at each iteration. This is traditionally done by computing the trace of the hat matrix which maps the data vector to its estimate. We prove some theoretical results concerning the hat matrix. One of them provides an upper bound on the increase of df from the m-th to the (m + 1)-th iteration. Based on the properties of the hat matrix, we propose novel ITC for selecting the number of iterations. All of them are obtained by modifying criteria designed for variable selection in the classical linear model. For assessing the performance of the novel criteria, we conduct a simulation study.

关键词： matching pursuit algorithm hat matrix projector information theoretic criteria number of iterations

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