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Continuation Newton methods with the residual trust-region time-stepping scheme for nonlinear equations
by
Xin-long, Luo
, Xiao, Hang
, Jia-hui, Lv
in
Continuation methods
/ Convergence
/ Mathematical analysis
/ Matlab
/ Methods
/ Newton methods
/ Nonlinear equations
/ Nonlinear systems
/ Polynomials
/ Subroutines
2021
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Continuation Newton methods with the residual trust-region time-stepping scheme for nonlinear equations
by
Xin-long, Luo
, Xiao, Hang
, Jia-hui, Lv
in
Continuation methods
/ Convergence
/ Mathematical analysis
/ Matlab
/ Methods
/ Newton methods
/ Nonlinear equations
/ Nonlinear systems
/ Polynomials
/ Subroutines
2021
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Do you wish to request the book?
Continuation Newton methods with the residual trust-region time-stepping scheme for nonlinear equations
by
Xin-long, Luo
, Xiao, Hang
, Jia-hui, Lv
in
Continuation methods
/ Convergence
/ Mathematical analysis
/ Matlab
/ Methods
/ Newton methods
/ Nonlinear equations
/ Nonlinear systems
/ Polynomials
/ Subroutines
2021
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Continuation Newton methods with the residual trust-region time-stepping scheme for nonlinear equations
Paper
Continuation Newton methods with the residual trust-region time-stepping scheme for nonlinear equations
2021
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Overview
For nonlinear equations, the homotopy methods (continuation methods) are popular in engineering fields since their convergence regions are large and they are quite reliable to find a solution. The disadvantage of the classical homotopy methods is that their computational time is heavy since they need to solve many auxiliary nonlinear systems during the intermediate continuation processes. In order to overcome this shortcoming, we consider the special explicit continuation Newton method with the residual trust-region time-stepping scheme for this problem. According to our numerical experiments, the new method is more robust and faster to find the required solution of the real-world problem than the traditional optimization method (the built-in subroutine fsolve.m of the MATLAB environment) and the homotopy continuation methods(HOMPACK90 and NAClab). Furthermore, we analyze the global convergence and the local superlinear convergence of the new method.
Publisher
Cornell University Library, arXiv.org
Subject
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