![Sample our Computer Science journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5928/TOC-Subject-Sample-2021-Computer-Science.jpg"})
Abstract
We propose a parallel version of the iteratively regularized Gauss–Newton method for solving a system of ill-posed equations. Under certain widely used assumptions, the convergence rate of the parallel method is established. Numerical experiments show that the parallel iteratively regularized Gauss–Newton method is computationally convenient for dealing with underdetermined systems of nonlinear equations on parallel computers, especially when the number of unknowns is much larger than that of equations.
Acknowledgement
The authors are grateful to the anonymous referees and Professor Qin Sheng, Editor-in-Chief of IJCM for their comments which substantially improved the quality of this paper. The authors express their sincere thanks to the Advanced Math Program of Ministry of Education and Training, Vietnam for sponsoring their working visit to University of Washington and the Department of Applied Mathematics, University of Washington for the hospitality. This work was partially supported by the Vietnam National Foundation for Science and Technology (NAFOSTED).