Results 1 to 10 of about 1,758,706 (251)

An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery

IEEE Access, 2021
Joint sparse recovery (JSR) in compressed sensing simultaneously recovers sparse signals with a common sparsity structure from their multiple measurement vectors obtained through a common sensing matrix.
Lili Pan, Xunzhi Zhu
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Nonconvex Penalized Regularization for Robust Sparse Recovery in the Presence of $S\alpha S$ Noise

IEEE Access, 2018
Nonconvex penalties have recently received considerable attention in sparse recovery based on Gaussian assumptions. However, many sparse recovery problems occur in the presence of impulsive noises. This paper is concerned with the analysis and comparison
Yunyi Li, Yun Lin, Xiefeng Cheng, Zhuolei Xiao, Feng Shu, Guan Gui   +5 more
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A Unified Feasible SQP Framework for sparse and non-negative sparse recovery

EURASIP Journal on Advances in Signal Processing
Sparse signal recovery is a central problem in many areas, including medical imaging, remote sensing, machine learning, and data science. In many practical settings, the underlying signal is inherently non-negative, due to the physical nature of the ...
Mohammad Saeid Alamdari, Masoud Fatemi
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A Simple Gaussian Measurement Bound for Exact Recovery of Block-Sparse Signals

Discrete Dynamics in Nature and Society, 2014
We present a probabilistic analysis on conditions of the exact recovery of block-sparse signals whose nonzero elements appear in fixed blocks. We mainly derive a simple lower bound on the necessary number of Gaussian measurements for exact recovery of ...
Zhi Han, Jianjun Wang, Jia Jing, Hai Zhang   +3 more
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Sparse ECG Denoising with Generalized Minimax Concave Penalty

Sensors, 2019
The electrocardiogram (ECG) is an important diagnostic tool for cardiovascular diseases. However, ECG signals are susceptible to noise, which may degenerate waveform and cause misdiagnosis.
Zhongyi Jin, Anming Dong, Minglei Shu, Yinglong Wang   +3 more
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An Efficient Sparse Recovery STAP Algorithm for Airborne Bistatic Radars Based on Atomic Selection under the Bayesian Framework

Remote Sensing
The traditional sparse recovery (SR) space-time adaptive processing (STAP) algorithms are greatly affected by grid mismatch, leading to poor performance in airborne bistatic radar clutter suppression.
Kun Liu, Tong Wang, Weijun Huang
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Efficient Sparse Recovery and Demixing Using Nonconvex Regularization

IEEE Access, 2019
Sparse demixing aims to separate signals that are sparse in some general dictionary, which has wide applications in signal and image processing, such as in super-resolution, image inpainting, robust sparse recovery, source separation, interference ...
Junhui Mei, Juntong Xi
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Robust Sparse Recovery in Impulsive Noise via M-Estimator and Non-Convex Regularization

IEEE Access, 2019
Robust sparse recovery aims at recovering a sparse signal or image from its compressed and contaminated measurements. Under the impulsive noise condition, the performance of traditional sparse recovery algorithms may deteriorate seriously for exploiting &
Le Gao, Dongjie Bi, Xifeng Li, Libiao Peng, Weijie Xu, Yongle Xie   +5 more
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A Survey on Nonconvex Regularization-Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

IEEE Access, 2018
In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen, Lei Chu, Peilin Liu, Robert C. Qiu   +3 more
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PN Codes Estimation of Binary Phase Shift Keying Signal Based on Sparse Recovery for Radar Jammer. [PDF]

Sensors (Basel), 2023
Peng B, Chen Q.
europepmc   +1 more source