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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE transactions on circuits and systems for video technology Ročník 35; číslo 6; s. 5367 - 5379
Hlavní autori:	He, Zihao, Shu, Qianyu, Wen, Jinming, Cheung So, Hing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.06.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!