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Journal of Scientific Computing

Erschienen in:

01.04.2021

Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction

verfasst von: Caiying Wu, Jing Wang, Jan Harold Alcantara, Jein-Shan Chen

Erschienen in: Journal of Scientific Computing | Ausgabe 1/2021

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Abstract

In this paper, we propose a new smoothing strategy along with conjugate gradient algorithm for the signal reconstruction problem. Theoretically, the proposed conjugate gradient algorithm along with the smoothing functions for the absolute value function is shown to possess some nice properties which guarantee global convergence. Numerical experiments and comparisons suggest that the proposed algorithm is an efficient approach for sparse recovery. Moreover, we demonstrate that the approach has some advantages over some existing solvers for the signal reconstruction problem.

Vorheriger Artikel Strong Convergence of Self-adaptive Inertial Algorithms for Solving Split Variational Inclusion Problems with Applications

Nächster Artikel A Global-in-time Domain Decomposition Method for the Coupled Nonlinear Stokes and Darcy Flows

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Titel: Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction
verfasst von: Caiying Wu
Jing Wang
Jan Harold Alcantara
Jein-Shan Chen
Publikationsdatum: 01.04.2021
Verlag: Springer US
Erschienen in: Journal of Scientific Computing / Ausgabe 1/2021
Print ISSN: 0885-7474
Elektronische ISSN: 1573-7691
DOI: https://doi.org/10.1007/s10915-021-01440-z

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