Du, X.P.[Xin-Peng],
Cheng, L.Z.[Li-Zhi],
Liu, L.F.[Lu-Feng],
A Swarm Intelligence Algorithm for Joint Sparse Recovery,
SPLetters(20), No. 6, 2013, pp. 611-614.
IEEE DOI
1307
Gaussian processes; compressed sensing theory
BibRef
Yu, X.,
Baek, S.J.,
Sufficient Conditions on Stable Recovery of Sparse Signals With Partial
Support Information,
SPLetters(20), No. 5, May 2013, pp. 539-542.
IEEE DOI
1304
BibRef
Chen, Z.,
Molina, R.,
Katsaggelos, A.K.,
Automated Recovery of Compressedly Observed Sparse Signals From
Smooth Background,
SPLetters(21), No. 8, August 2014, pp. 1012-1016.
IEEE DOI
1406
Algorithm design and analysis
BibRef
Foucart, S.,
Koslicki, D.,
Sparse Recovery by Means of Nonnegative Least Squares,
SPLetters(21), No. 4, April 2014, pp. 498-502.
IEEE DOI
1403
Compressed sensing
BibRef
Dziwoki, G.,
Averaged Properties of the Residual Error in Sparse Signal
Reconstruction,
SPLetters(23), No. 9, September 2016, pp. 1170-1173.
IEEE DOI
1609
Gaussian processes
BibRef
Choi, J.,
Successive Hypothesis Testing Based Sparse Signal Recovery and Its
Application to MUD in Random Access,
SPLetters(24), No. 2, February 2017, pp. 166-170.
IEEE DOI
1702
compressed sensing
BibRef
Foucart, S.,
Lecué, G.,
An IHT Algorithm for Sparse Recovery From Subexponential Measurements,
SPLetters(24), No. 9, September 2017, pp. 1280-1283.
IEEE DOI
1708
compressed sensing,
minimisation, probability, IHT algorithm,
classical restricted isometry property,
independent subexponential random variables,
L1-minimization, matrix, probability,
subexponential measurements, uniform sparse recovery,
Compressive sensing,
restricted isometry property, sparse recovery, subexponential
random variable
BibRef
Wen, Z.D.[Zai-Dao],
Hou, B.[Biao],
Jiao, L.C.[Li-Cheng],
Joint Sparse Recovery With Semisupervised MUSIC,
SPLetters(24), No. 5, May 2017, pp. 629-633.
IEEE DOI
1704
MUSIC: multiple signal classification.
compressed sensing
BibRef
Rateb, A.M.,
Syed-Yusof, S.K.,
Rashid, R.A.,
On the Impact of Prefiltering on Compressed Sensing in Presence of
Invalid Measurements,
SPLetters(24), No. 12, December 2017, pp. 1886-1890.
IEEE DOI
1712
Compressed sensing, Current measurement, Gain measurement, Minimization,
Noise measurement, Random variables, Sensors, sparse recovery
BibRef
Li, F.,
Hong, S.,
Gu, Y.,
Wang, L.,
An Optimization-Oriented Algorithm for Sparse Signal Reconstruction,
SPLetters(26), No. 3, March 2019, pp. 515-519.
IEEE DOI
1903
compressed sensing, computational complexity, greedy algorithms,
optimisation, search problems, signal reconstruction,
optimization-oriented algorithm
BibRef
Daei, S.[Sajad],
Haddadi, F.[Farzan],
Amini, A.[Arash],
Distribution-Aware Block-Sparse Recovery via Convex Optimization,
SPLetters(26), No. 4, April 2019, pp. 528-532.
IEEE DOI
1903
Bayes methods, compressed sensing, convex programming, probability,
signal reconstruction, signal sampling, block-sparse signal,
convex optimization
BibRef
Wang, Q.[Qian],
Qu, G.R.[Gang-Rong],
Han, G.H.[Guang-Hui],
A thresholding algorithm for sparse recovery via Laplace norm,
SIViP(13), No. 2, March 2019, pp. 389-395.
Springer DOI
1904
Recovery of signal from sparse input.
BibRef
Hezave, H.,
Javadzadeh, M.,
Kahaei, M.H.[Mohammad Hossein],
Sparse Signal Reconstruction Using Blind Super-Resolution With
Arbitrary Sampling,
SPLetters(27), 2020, pp. 615-619.
IEEE DOI
2005
Frequency modulation, Signal resolution, Deconvolution,
Image resolution, Wave functions, Compressed sensing,
joint spectral sparsity
BibRef
Nareddy, K.K.R.[Kartheek Kumar Reddy],
Kamath, A.J.[Abijith Jagannath],
Seelamantula, C.S.[Chandra Sekhar],
Tight-Frame-Like Analysis-Sparse Recovery Using Nontight Sensing
Matrices,
SIIMS(17), No. 3, 2024, pp. 1587-1618.
DOI Link
2501
BibRef
He, Z.[Zihao],
Shu, Q.Y.[Qian-Yu],
Wen, J.M.[Jin-Ming],
So, H.C.[Hing Cheung],
Efficient Sparse Recovery With Arctangent Regularization:
A Novel Iterative Thresholding Algorithm,
CirSysVideo(35), No. 6, June 2025, pp. 5367-5379.
IEEE DOI
2506
Approximation algorithms, Vectors, Iterative algorithms, Convex functions,
Convergence, Tensors, Sensors, Polynomials, Noise, sparse recovery
BibRef
Zhang, J.F.[Jin-Feng],
Huang, Y.X.[Yu-Xun],
Liao, B.[Bin],
Hu, Y.H.[Yao-Hua],
Momentum-Based Hard Thresholding Pursuit for Sparse Signal Recovery,
SPLetters(33), 2026, pp. 2500-2504.
IEEE DOI
2607
Thresholding (Imaging), Algorithms, Convergence, Vectors,
Measurement, Matrices, Compressed sensing, Compressed sensing,
sparse recovery
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Snapshot Compressive Sensing .