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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Veröffentlicht in:	Digital signal processing Jg. 164; S. 105246
Hauptverfasser:	Zhou, Xin, Liu, Zhen, Zhang, Haisu, Zhao, Zhiyuan, Liu, Yongxiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.09.2025
Schlagworte:	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
Online-Zugang:	Volltext
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