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Global Convergence Properties of the Modified Bfgs Method Associating with General Line Search Model
| Content Provider | Semantic Scholar |
|---|---|
| Author | Liu, Jingmei Guo, Qiang |
| Abstract | To the unconstrained programme of non-convex function, this article give a modified BFGS algorithm. The idea of the algorithm is to modify the approximate Hessian matrix for obtaining the descent direction and guaranteeing the efficacious of the quasi-Newton iteration pattern. We prove the global convergence properties of the algorithm associating with the general form of line search, and prove the quadratic convergence rate of the algorithm under some conditions. AMS Mathematics Subject Classification : 65H10, 65F10. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://icms.kaist.ac.kr/mathnet/kms_tex/981646.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Approximation algorithm Broyden–Fletcher–Goldfarb–Shanno algorithm Convergence (action) Convex function Descent direction Hessian Iteration Line search Local convergence Mathematics Subject Classification Newton's method Rate of convergence VHDL-AMS |
| Content Type | Text |
| Resource Type | Article |
