On the Convergence of the Iterative Shrinkage/Thresholding Algorithm With a Weakly Convex Penalty

We consider the iterative shrinkage/thresholding algorithm (ISTA) applied to a cost function composed of a data fidelity term and a penalty term. The penalty is nonconvex but the concavity of the penalty is accounted for by the data fidelity term so that the overall cost function is convex. We provi...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 64; H. 6; S. 1597 - 1608
1. Verfasser:	Bayram, Ilker
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 15.03.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Acceleration Convergence Convex functions Cost function Forward backward splitting Iterative algorithms iterative shrinkage/thresholding majorization minimization Minimization Signal processing algorithms weakly convex
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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