期刊
COMPUTERS & MATHEMATICS WITH APPLICATIONS
卷 70, 期 10, 页码 2442-2453出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.camwa.2015.09.014
关键词
Monotone nonlinear equations; Projection method; Conjugate gradient method; Compressive sensing
资金
- National Natural Science Foundation of China [11171362, 11571055]
- Specialized Research Fund for the Doctoral Program of Higher Education [20120191110031]
- Scientific and Technological Research Program of Chongqing Municipal Education Commission [KJ1501003]
In this paper, we present a projection method to solve monotone nonlinear equations with convex constraints. This method can be viewed as an extension of CG_DESCENT method which is one of the most effective conjugate gradient methods for solving unconstrained optimization problems. Because of derivative-free and low storage, the proposed method can be used to solve large-scale nonsmooth monotone nonlinear equations. Its global convergence is established under some appropriate conditions. Preliminary numerical results show that the proposed method is effective and promising. Moreover, we also successfully use the proposed method to solve the sparse signal reconstruction in compressive sensing. (C) 2015 Elsevier Ltd. All rights reserved.
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