Iterative shrinkage-thresholding algorithm with inertia and dry friction for convolutional dictionary learning

The iterative shrinkage-thresholding algorithm (ISTA) is often used to address the convolutional dictionary learning problem. However, the ISTA algorithm is easy to fall into the local minimum, and some atoms in the convolution dictionary change little when updated. Therefore, in this paper, we prop...

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Veröffentlicht in:	Digital signal processing Jg. 140; S. 104139
Hauptverfasser:	Li, Pengyu, Zhang, Yali, Li, Ze, Wang, Jinjia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.08.2023
Schlagworte:	Convolutional dictionary learning Dry friction Finite convergence Inertia algorithm Iterative shrinkage-thresholding algorithm Finite convergence Iterative shrinkage-thresholding algorithm Convolutional dictionary learning Inertia algorithm Dry friction
ISSN:	1051-2004, 1095-4333
Online-Zugang:	Volltext
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