Results 151 to 160 of about 3,975 (201)

Super-Resolution Reconstruction of Remote Sensing Images Using Chaotic Mapping to Optimize Sparse Representation. [PDF]

Sensors (Basel)
Fang H, Zheng L, Xu W.
europepmc   +1 more source

The application of compressed sensing on tumor mutation burden calculation from overlapped pooling sequencing data. [PDF]

BMC Bioinformatics
Cui Y, Qiao Y, An R, Pan X, Tu J.
europepmc   +1 more source

Adaptive Channel Estimation for Semi-Passive IRS with Optimized Sensor Deployment. [PDF]

Sensors (Basel)
Han Z, Wang H, Wang Y, Fan Z.
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An Improved OMP Algorithm for Enhancing the Anti-Interference Performance of Array Antennas. [PDF]

Sensors (Basel)
Gao M, Zhang Y, Yu Y, Lv D, Xi R, Li W, Gu L, Wang Z.   +7 more
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Sensing dictionary construction for orthogonal matching pursuit algorithm in compressive sensing

, 2013
Bo Li
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Sparse stability diagrams of LSCF method via strategic pole destabilization using orthogonal matching pursuit [PDF]

Shogo Shimada, Akira Saito
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Sparse Orthogonal Matching Pursuit-based Parameter Estimation for Integrated Sensing and Communications [PDF]

Ngoc-Son Duong, Khac–Hoang Ngo, Thai-Mai Thi Dinh, Van-Linh Nguyen   +3 more
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Online search Orthogonal Matching Pursuit

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012
The recovery of a sparse signal x from y= Φx, where Φ is a matrix with more columns than rows, is a task central to many signal processing problems. In this paper we present a new greedy algorithm to solve this type of problem. Our approach leverages ideas from the field of online search on state spaces.
Alejandro J. Weinstein, Michael B. Wakin
openaire   +1 more source

Randomized simultaneous orthogonal matching pursuit

2015 23rd European Signal Processing Conference (EUSIPCO), 2015
In this paper, we develop randomized simultaneous orthogonal matching pursuit (RandSOMP) algorithm which computes an approximation of the Bayesian minimum mean-squared error (MMSE) estimate of an unknown rowsparse signal matrix. The approximation is based on greedy iterations, as in SOMP, and it elegantly incorporates the prior knowledge of the ...
Aqib Ejaz, Esa Ollila, Visa Koivunen
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