Deep Learning Approach Based on Tensor-Train for Sparse Signal Recovery

IEEE Access ◽

10.1109/access.2019.2903906 ◽

2019 ◽

Vol 7 ◽

pp. 34753-34761

Author(s):

Cong Zou ◽

Fang Yang

Keyword(s):

Deep Learning ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Learning Approach

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Decentralized Joint-Sparse Signal Recovery: A Sparse Bayesian Learning Approach

IEEE Transactions on Signal and Information Processing over Networks ◽

10.1109/tsipn.2016.2612120 ◽

2017 ◽

Vol 3 (1) ◽

pp. 29-45 ◽

Author(s):

Saurabh Khanna ◽

Chandra R. Murthy

Keyword(s):

Bayesian Learning ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Learning Approach ◽

Sparse Bayesian Learning

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Jointly Sparse Signal Recovery and Support Recovery via Deep Learning with Applications in MIMO-based Grant-Free Random Access

IEEE Journal on Selected Areas in Communications ◽

10.1109/jsac.2020.3018802 ◽

2020 ◽

pp. 1-1 ◽

Author(s):

Ying Cui ◽

Shuaichao Li ◽

Wanqing Zhang

Keyword(s):

Deep Learning ◽

Random Access ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Support Recovery

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Spectrally Sparse Signal Recovery via Hankel Matrix Completion With Prior Information

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2021.3067738 ◽

2021 ◽

Vol 69 ◽

pp. 2174-2187

Author(s):

Xu Zhang ◽

Yulong Liu ◽

Wei Cui

Keyword(s):

Prior Information ◽

Matrix Completion ◽

Hankel Matrix ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery

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Sparse Signal Recovery for Multiple Measurement Vectors with Temporally Correlated Entries

Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing ◽

10.1145/3293353.3293420 ◽

2018 ◽

Author(s):

Shruti Sharma ◽

Santanu Chaudhury ◽

Jayadeva Jayadeva ◽

Snigdha Bhagat

Keyword(s):

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Multiple Measurement ◽

Multiple Measurement Vectors ◽

Temporally Correlated

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Uncertainty Relations and Sparse Signal Recovery

Information-Theoretic Methods in Data Science ◽

10.1017/9781108616799.007 ◽

2021 ◽

pp. 163-196

Author(s):

Erwin Riegler ◽

Helmut Bökei

Keyword(s):

Sparse Signal ◽

Sparse Signal Recovery ◽

Uncertainty Relations ◽

Signal Recovery

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Sparse signal recovery based on adaptive algorithms for debris detector

AIP Advances ◽

10.1063/5.0050715 ◽

2021 ◽

Vol 11 (6) ◽

pp. 065131

Author(s):

Bingsen Xue ◽

Xingming Zhang ◽

Yunzhe Xu ◽

Yehui Li ◽

Hongpeng Zhang ◽

...

Keyword(s):

Adaptive Algorithms ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery

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DeepFPC: A deep unfolded network for sparse signal recovery from 1-Bit measurements with application to DOA estimation

Signal Processing ◽

10.1016/j.sigpro.2020.107699 ◽

2020 ◽

Vol 176 ◽

pp. 107699

Author(s):

Peng Xiao ◽

Bin Liao ◽

Nikos Deligiannis

Keyword(s):

Doa Estimation ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery

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Sparse signal recovery via infimal convolution based penalty

Signal Processing Image Communication ◽

10.1016/j.image.2021.116214 ◽

2021 ◽

Vol 94 ◽

pp. 116214

Author(s):

Lin Lei ◽

Yuli Sun ◽

Xiao Li

Keyword(s):

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Infimal Convolution

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Type I and Type II Bayesian Methods for Sparse Signal Recovery Using Scale Mixtures

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2016.2546231 ◽

2016 ◽

Vol 64 (13) ◽

pp. 3418-3428 ◽

Author(s):

Ritwik Giri ◽

Bhaskar Rao

Keyword(s):

Bayesian Methods ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Type I ◽

Type Ii ◽

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Improved RIP‐based performance guarantee for sparse signal recovery via A*OMP

Electronics Letters ◽

10.1049/el.2018.5211 ◽

2018 ◽

Vol 54 (21) ◽

pp. 1216-1218 ◽

Author(s):

Haifeng Li ◽

Guoqi Liu ◽

Jian Zou

Keyword(s):

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Performance Guarantee

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