Key parameters for iterative thresholding-type algorithm with nonconvex regularization

Iterative thresholding-type algorithm, as one of the typical methods of compressed sensing (CS) theory, is widely used in sparse recovery field, because of its simple computational process. However, the estimation accuracy and convergence speed achieved by this type of algorithm with a nonconvex reg...

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Vydané v:	Digital signal processing Ročník 164; s. 105246
Hlavní autori:	Zhou, Xin, Liu, Zhen, Zhang, Haisu, Zhao, Zhiyuan, Liu, Yongxiang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.09.2025
Predmet:	Compressive sensing (CS) Fast iterative shrinkage-thresholding algorithm (FISTA) Iterative half thresholding (IHalfT) Iterative hard thresholding (IHT) Iterative soft thresholding (IST) Normalized iterative hard thresholding (NIHT) Normalized iterative hard thresholding (NIHT) Iterative soft thresholding (IST) Iterative half thresholding (IHalfT) Fast iterative shrinkage-thresholding algorithm (FISTA) Compressive sensing (CS) Iterative hard thresholding (IHT)
ISSN:	1051-2004
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