EEG Monitoring: Performance Comparison of Compressive Sensing Reconstruction Algorithms

Advances in Intelligent Systems and Computing - Information Systems Design and Intelligent Applications ◽

10.1007/978-981-13-3329-3_2 ◽

2018 ◽

pp. 9-17 ◽

Cited By ~ 2

Author(s):

Meenu Rani ◽

S. B. Dhok ◽

R. B. Deshmukh

Keyword(s):

Compressive Sensing ◽

Performance Comparison ◽

Eeg Monitoring ◽

Reconstruction Algorithms ◽

Monitoring Performance

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Performance Comparison of Orthogonal Matching Pursuit and Novel Incremental Gaussian Elimination OMP Reconstruction Algorithms for Compressive Sensing

10.1109/comcas52219.2021.9629027 ◽

2021 ◽

Author(s):

V H Prasad Reddy ◽

Puli Kishore Kumar

Keyword(s):

Compressive Sensing ◽

Matching Pursuit ◽

Gaussian Elimination ◽

Performance Comparison ◽

Orthogonal Matching Pursuit ◽

Reconstruction Algorithms

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Compressive Sensing-Based Continuous EEG Monitoring: Seizure Detection Performance Comparison of Different Classifiers

Lecture Notes in Electrical Engineering - Advances in VLSI, Communication, and Signal Processing ◽

10.1007/978-981-15-6840-4_37 ◽

2020 ◽

pp. 459-468

Author(s):

Meenu Rani ◽

S. B. Dhok ◽

R. B. Deshmukh

Keyword(s):

Compressive Sensing ◽

Seizure Detection ◽

Performance Comparison ◽

Detection Performance ◽

Eeg Monitoring ◽

Continuous Eeg ◽

Continuous Eeg Monitoring

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Performance Comparison of Reconstruction Algorithms in Compressive Sensing Based Single Snapshot DOA Estimation

IETE Journal of Research ◽

10.1080/03772063.2020.1732840 ◽

2020 ◽

pp. 1-9

Author(s):

Kankanala Srinivas ◽

Saurav Ganguly ◽

Puli Kishore Kumar

Keyword(s):

Compressive Sensing ◽

Doa Estimation ◽

Performance Comparison ◽

Reconstruction Algorithms ◽

Single Snapshot

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Compressive sensing: Performance comparison of sparse recovery algorithms

2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC) ◽

10.1109/ccwc.2017.7868430 ◽

2017 ◽

Cited By ~ 21

Author(s):

Youness Arjoune ◽

Naima Kaabouch ◽

Hassan El Ghazi ◽

Ahmed Tamtaoui

Keyword(s):

Compressive Sensing ◽

Sparse Recovery ◽

Performance Comparison ◽

Recovery Algorithms ◽

Sensing Performance

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Computational performance comparison of wavefront reconstruction algorithms for the European Extremely Large Telescope on multi-CPU architecture

Applied Optics ◽

10.1364/ao.51.003564 ◽

2012 ◽

Vol 51 (16) ◽

pp. 3564 ◽

Cited By ~ 2

Author(s):

Lu Feng ◽

Enrico Fedrigo ◽

Clémentine Béchet ◽

Elisabeth Brunner ◽

Werther Pirani

Keyword(s):

Performance Comparison ◽

Reconstruction Algorithms ◽

Large Telescope ◽

Wavefront Reconstruction ◽

Computational Performance

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Object-dependent performance comparison of two iterative reconstruction algorithms

IEEE Transactions on Nuclear Science ◽

10.1109/23.12797 ◽

1988 ◽

Vol 35 (1) ◽

pp. 611-614 ◽

Cited By ~ 28

Author(s):

J.A. Stamos ◽

W.L. Rogers ◽

N.H. Clinthorne ◽

K.F. Koral

Keyword(s):

Iterative Reconstruction ◽

Performance Comparison ◽

Reconstruction Algorithms

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Assessment of robust reconstruction algorithms for compressive sensing spectral-domain optical coherence tomography

10.1117/12.2002476 ◽

2013 ◽

Cited By ~ 2

Author(s):

Daguang Xu ◽

Yong Huang ◽

Jin U. Kang

Keyword(s):

Optical Coherence Tomography ◽

Compressive Sensing ◽

Spectral Domain ◽

Optical Coherence ◽

Reconstruction Algorithms

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Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

Physics in Medicine and Biology ◽

10.1088/0031-9155/54/19/008 ◽

2009 ◽

Vol 54 (19) ◽

pp. 5781-5804 ◽

Cited By ~ 204

Author(s):

Jie Tang ◽

Brian E Nett ◽

Guang-Hong Chen

Keyword(s):

Compressed Sensing ◽

Total Variation ◽

Iterative Reconstruction ◽

Performance Comparison ◽

Reconstruction Algorithms ◽

Statistical Iterative Reconstruction

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Performance comparison of representative model-based fault reconstruction algorithms for aircraft sensor fault detection and diagnosis

Aerospace Science and Technology ◽

10.1016/j.ast.2019.105649 ◽

2020 ◽

Vol 98 ◽

pp. 105649 ◽

Cited By ~ 2

Author(s):

Qizhi He ◽

Weiguo Zhang ◽

Peng Lu ◽

Jinglong Liu

Keyword(s):

Fault Detection ◽

Performance Comparison ◽

Fault Detection And Diagnosis ◽

Reconstruction Algorithms ◽

Sensor Fault ◽

Model Based ◽

Fault Reconstruction ◽

Sensor Fault Detection ◽

Representative Model ◽

Detection And Diagnosis

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1-Bit Compressive Data Gathering for Wireless Sensor Networks

Journal of Sensors ◽

10.1155/2014/805423 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 6

Author(s):

Jiping Xiong ◽

Qinghua Tang

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Compressive Sensing ◽

State Of The Art ◽

Data Gathering ◽

Reconstruction Algorithm ◽

Experimental Results ◽

Wireless Sensor ◽

Communication Overhead ◽

Reconstruction Algorithms

Compressive sensing (CS) has been widely used in wireless sensor networks for the purpose of reducing the data gathering communication overhead in recent years. In this paper, we firstly apply 1-bit compressive sensing to wireless sensor networks to further reduce the communication overhead that each sensor needs to send. Furthermore, we propose a novel blind 1-bit CS reconstruction algorithm which outperforms other state-of-the-art blind 1-bit CS reconstruction algorithms under the settings of WSN. Experimental results on real sensor datasets demonstrate the efficiency of our method.

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