New family of conjugate gradient methods with sufficient descent condition and global convergence for unconstrained optimizations
Conjugate gradient methods are a family of significance methods for solving of large-scale unconstrained optimization problems. This is due to both the simplicity of its algorithm and low memory requirement. A lot of efforts have been done to improve those methods since 1964 when the work of Flet...
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| Format: | Thesis Book |
| Language: | English |
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Tembila UniSZA Thesis Collection
| Call Number: |
QA218 I27 2015 |
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| Accession | Item Category | Format | Status | Notes |
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| 1000167576 | Reference | Thesis | Available |