Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4631492 | Applied Mathematics and Computation | 2011 | 13 Pages |
Abstract
Many constrained sets in problems such as signal processing and optimal control can be represented as a fixed point set of a certain nonexpansive mapping, and a number of iterative algorithms have been presented for solving a convex optimization problem over a fixed point set. This paper presents a novel gradient method with a three-term conjugate gradient direction that is used to accelerate conjugate gradient methods for solving unconstrained optimization problems. It is guaranteed that the algorithm strongly converges to the solution to the problem under the standard assumptions. Numerical comparisons with the existing gradient methods demonstrate the effectiveness and fast convergence of this algorithm.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Hideaki Iiduka,