$Nonconvex Penalized Regularization for Robust Sparse Recovery in the Presence of S\alpha S Noise$

Nonconvex Penalized Regularization for Robust Sparse Recovery in the Presence of S\alpha S Noise

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 of different sparsity-inducing penalties for...

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Veröffentlicht in:	IEEE access 2018-01, Vol.6, p.25474-25485
Hauptverfasser:	Li, Yunyi, Lin, Yun, Cheng, Xiefeng, Xiao, Zhuolei, Shu, Feng, Gui, Guan
Format:	Artikel
Sprache:	eng
Schlagworte:	alternating direction method of multipliers (ADMM) Convex functions Image restoration impulsive noise Iterative algorithms Noise measurement Nonconvex penalties Optimization robust sparse recovery Robustness Telecommunications
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