Results 41 to 50 of about 46,224 (313)
Peak Colocalized Orthogonal Matching Pursuit for Seismic Trace Decomposition
IEEE Access, 2020 Orthogonal matching pursuit (OMP) is an efficient method for decomposing a seismic trace with regard to an atom dictionary. The original OMP optimizes one unique single objective in terms of successively maximizing the inner product between an atom and ...
Yongqing Li, Jun Wang, Hui Li, Peng Ren
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Channel Estimation Method of OFDM System based on Compressed Sensing
Guangtongxin yanjiu, 2022 Aiming at the time-domain sparsity and unknown sparsity of wireless channels, compressed sensing technology is applied to the channel estimation of Orthogonal Frequency Division Multiplexing (OFDM) system. This paper proposes a sparsity adaptive matching
LI Gui-yong +4 more
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Recovery of Sparse Signals via Modified Hard Thresholding Pursuit Algorithms
IET Signal Processing, 2023 In this paper, we propose a modified version of the hard thresholding pursuit algorithm, called modified hard thresholding pursuit (MHTP), using a convex combination of the current and previous points.
Li-Ping Geng +3 more
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Sparse Representation of Astronomical Images [PDF]
, 2012 Sparse representation of astronomical images is discussed. It is shown that a significant gain in sparsity is achieved when particular mixed dictionaries are used for approximating these types of images with greedy selection strategies.
Andrle +22 more
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TV-min and Greedy Pursuit for Constrained Joint Sparsity and Application to Inverse Scattering [PDF]
, 2012 This paper proposes a general framework for compressed sensing of constrained joint sparsity (CJS) which includes total variation minimization (TV-min) as an example.
Fannjiang, Albert
core +5 more sources
A note on orthogonal matching pursuit under restricted isometry property
IET Signal Processing, 2022 The orthogonal matching pursuit (OMP) algorithm is a classical greedy algorithm widely used in compressed sensing. The number of iterations required for the OMP algorithm to perform exact the recovery of sparse signals is a fundamental problem in signal ...
Xueping Chen +3 more
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Orthogonal Matching Pursuit Under the Restricted Isometry Property [PDF]
Constructive Approximation, 2016 12 ...
Albert Cohen +2 more
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Perturbed block orthogonal matching pursuit
Electronics Letters, 2018 The block orthogonal matching pursuit (BOMP) algorithm is an efficient method in compressed sensing (CS) for the reconstruction of block‐sparse signals, whose non‐zero entries occur in clusters. However, due to the non‐ideal factors in practice, there exits perturbation in the CS system, which may cause significant performance degradation during ...
Yupeng Cui +3 more
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, 2019 We show the potential of greedy recovery strategies for the sparse approximation of multivariate functions from a small dataset of pointwise evaluations by considering an extension of the orthogonal matching pursuit to the setting of weighted sparsity ...
A Chkifa +10 more
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Relaxed Recovery Conditions for OMP/OLS by Exploiting both Coherence and Decay [PDF]
, 2015 We propose extended coherence-based conditions for exact sparse support recovery using orthogonal matching pursuit (OMP) and orthogonal least squares (OLS).
Drémeau, Angélique +2 more
core +3 more sources