Open Access
2014 Nonmonotone Adaptive Barzilai-Borwein Gradient Algorithm for Compressed Sensing
Yuanying Qiu, Jianlei Yan, Fanyong Xu
Abstr. Appl. Anal. 2014(SI43): 1-6 (2014). DOI: 10.1155/2014/410104

Abstract

We study a nonmonotone adaptive Barzilai-Borwein gradient algorithm for l 1 -norm minimization problems arising from compressed sensing. At each iteration, the generated search direction enjoys descent property and can be easily derived by minimizing a local approximal quadratic model and simultaneously taking the favorable structure of the l 1 -norm. Under some suitable conditions, its global convergence result could be established. Numerical results illustrate that the proposed method is promising and competitive with the existing algorithms NBBL1 and TwIST.

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Yuanying Qiu. Jianlei Yan. Fanyong Xu. "Nonmonotone Adaptive Barzilai-Borwein Gradient Algorithm for Compressed Sensing." Abstr. Appl. Anal. 2014 (SI43) 1 - 6, 2014. https://doi.org/10.1155/2014/410104

Information

Published: 2014
First available in Project Euclid: 2 October 2014

MathSciNet: MR3198186
zbMATH: 07022340
Digital Object Identifier: 10.1155/2014/410104

Rights: Copyright © 2014 Hindawi

Vol.2014 • No. SI43 • 2014
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