Signal recovery with convex constrained nonlinear monotone equations through conjugate gradient hybrid approach
| Autor: | Abubakar Sani Halilu, Mohammed Yusuf Waziri, Kabiru Ahmed, Arunava Majumder |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Numerical Analysis
Line search General Computer Science Computer science Applied Mathematics 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Regularization (mathematics) Projection (linear algebra) Theoretical Computer Science Nonlinear system symbols.namesake Monotone polygon Modeling and Simulation Norm (mathematics) Conjugate gradient method Jacobian matrix and determinant 0202 electrical engineering electronic engineering information engineering symbols Applied mathematics 020201 artificial intelligence & image processing 0101 mathematics |
| Zdroj: | Mathematics and Computers in Simulation. 187:520-539 |
| ISSN: | 0378-4754 |
| DOI: | 10.1016/j.matcom.2021.03.020 |
| Popis: | In recent years there is a vast application of conjugate gradient methods to restore the disturbed signals in compressive sensing. This research aims at developing a scheme, which is more effective for restoring disturbed signals than the popular PCG method (Liu & Li, 2015). To realize the desired goal, a new conjugate gradient approach combined with the projection scheme of Solodov and Svaiter [Kluwer Academic Publishers, pp. 355-369(1998)] for solving monotone nonlinear equations with convex constraints is presented. The main idea employed in this algorithm is to approximate the Jacobian matrix via acceleration parameter in order to propose an effective conjugate gradient parameter. In addition, the step length is calculated using inexact line search technique. The proposed approach is proved to converge globally under some mild conditions . The numerical experiment, depicts the efficacy our method. Apart from generating search directions that are vital for global convergence, a significant contribution of the new method lies in its applications to solve the l 1 -norm regularization problem in signal recovery. Experiments with the scheme and the effective PCG solver, existing in the previous literature, shows that the new method provides much better results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect