Efficient Sparse Recovery With Arctangent Regularization: A Novel Iterative Thresholding Algorithm

Several existing works have revealed the effectiveness of arctangent-type penalties in exploiting sparsity for compressed sensing. However, addressing the subproblems associated with the arctangent penalty incurs considerable computational cost. Aiming to reduce complexity, we derive the closed-form...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology Jg. 35; H. 6; S. 5367 - 5379
Hauptverfasser:	He, Zihao, Shu, Qianyu, Wen, Jinming, Cheung So, Hing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms arctangent penalty Compressed sensing Computational efficiency Convergence Convex functions Costs Hyperbolic functions Iterative algorithms Noise Phase transitions Polynomials Recovery Regularization Sensors sparse recovery Tensors thresholding algorithm Vectors
ISSN:	1051-8215, 1558-2205
Online-Zugang:	Volltext
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