Department of Mathematics, Faculty of Science, Fixed Point Research Laboratory, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
Department of Mathematics, Faculty of Science, Fixed Point Research Laboratory, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
Punnarai Siricharoen
Center of Excellence in Theoretical and Computational Science Center (TaCS-CoE), Fixed Point Theory and Applications Research Group, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
Department of Mathematics, Faculty of Science, Fixed Point Research Laboratory, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
Department of Mathematics, Faculty of Science, Fixed Point Research Laboratory, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
In this article, we propose a modified conjugate descent (CD) projection algorithm for solving system of nonlinear monotone equations with convex constraints. The search direction in this algorithm use a convex combination of the steepest descent algorithm and the well-known CD method. The algorithm proves to be quite efficient for solving large scale monotone nonlinear equations, as it has low storage requirement and does not need the computation of Jacobian matrix. We prove the convergence of the algorithm using some conditions, and perform numerical experiments on some test problems. In order to show the efficiency of our proposed algorithm, the numerical performance is compared with some existing algorithms. Finally, by reformulating ℓ2 regularized problem into monotone equation, we successfully apply the algorithm to restore some blurred images. The numerical results obtained prove that the algorithm can be used as an efficient and qualitative solver for image restoration problems.
