2007/12/10 by Wanyou Cheng
Engineering · Mathematics · #Advanced Optimization Algorithms Research #Iterative Methods for Nonlinear Equations #Sparse and Compressive Sensing Techniques
paper · doi:10.1080/01630560701749524
openalex publication_date 2007/12/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
In this paper, by the use of the project of the PRP (Polak–Ribiére–Polyak) conjugate gradient direction, we develop a PRP-based descent method for solving unconstrained optimization problem. The method provides a sufficient descent direction for the objective function. Moreover, if exact line search is used, the method reduces to the standard PRP method. Under suitable conditions, we show that the method with some backtracking line search or the generalized Wolfe-type line search is globally convergent. We also report some numerical results and compare the performance of the method with some existing conjugate gradient methods. The results show that the proposed method is efficient.