A family of conjugate gradient methods for large-scale nonlinear equations
Dexiang Feng1,2, Min Sun3, Xueyong Wang3
1School of Management Sciences, Fudan University, Shanghai, China.
Abstract:
In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
Related Concept Videos
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Newton’s Method
Linear Differential Equations
Application of Nonlinear Inequalities
Differential Equations: Problem Solving
Separable Differential Equations

