Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations
Abstract In this paper, we propose a self adaptive spectral conjugate gradient-based projection method for systems of nonlinear monotone equations. Based on its modest memory requirement and its efficiency, the method is suitable for solving large-scale equations. We show that the method satisfies t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2020-01-01
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| Series: | Journal of the Egyptian Mathematical Society |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42787-019-0066-1 |
| Summary: | Abstract In this paper, we propose a self adaptive spectral conjugate gradient-based projection method for systems of nonlinear monotone equations. Based on its modest memory requirement and its efficiency, the method is suitable for solving large-scale equations. We show that the method satisfies the descent condition FkTdk≤−c∥Fk∥2,c>0 $F_{k}^{T}d_{k}\leq -c\|F_{k}\|^{2}, c>0$, and also prove its global convergence. The method is compared to other existing methods on a set of benchmark test problems and results show that the method is very efficient and therefore promising. |
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| ISSN: | 2090-9128 |