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Numerical Algorithms
Erschienen in: Numerical Algorithms 3/2023

14.07.2022 | Original Paper

A modified inertial three-term conjugate gradient projection method for constrained nonlinear equations with applications in compressed sensing

verfasst von: Guodong Ma, Jiachen Jin, Jinbao Jian, Jianghua Yin, Daolan Han

Erschienen in: Numerical Algorithms | Ausgabe 3/2023

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Abstract

In this paper, based on the three-term conjugate gradient projection method and the inertial technique, we propose a modified inertial three-term conjugate gradient projection method for solving nonlinear monotone equations with convex constraints. Embedding the inertial extrapolation step in the design for the search direction, the resulting direction satisfies the sufficient descent property which is independent of any line search rules. The global convergence and Q-linear convergence rate of the proposed algorithm are established under standard conditions. Numerical comparisons with three existing methods demonstrate that the proposed algorithm possesses superior numerical performance and good robustness for solving large-scale equations. Finally, the proposed method is applied to solve the sparse signal problems and image restoration in compressed sensing.
Vorheriger Artikel An upwind DG scheme preserving the maximum principle for the convective Cahn-Hilliard model
Nächster Artikel Unconditionally optimal H1-error estimate of a fast nonuniform L2-1σ scheme for nonlinear subdiffusion equations

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Metadaten
Titel
A modified inertial three-term conjugate gradient projection method for constrained nonlinear equations with applications in compressed sensing
verfasst von
Guodong Ma
Jiachen Jin
Jinbao Jian
Jianghua Yin
Daolan Han
Publikationsdatum
14.07.2022
Verlag
Springer US
Erschienen in
Numerical Algorithms / Ausgabe 3/2023
Print ISSN: 1017-1398
Elektronische ISSN: 1572-9265
DOI
https://doi.org/10.1007/s11075-022-01356-1

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