Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4958818 | Computers & Mathematics with Applications | 2017 | 7 Pages |
Abstract
Conjugate gradient method, as an efficient method, is used to solve unconstrained optimization problems. In this paper, we propose a class of modified Fletcher-Reeves conjugate gradient method, with Armijo-type line search, which generates the direction is descent for the objective function. Under mild conditions, we give that the proposed method is descent and globally convergent. Moreover, the method is applied to nonnegative matrix factorization, and the experimental results demonstrate the validity of the proposed method.
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Computer Science (General)
Authors
Xiangli Li, Wen Zhang, Xiaoliang Dong,