Block and asynchronous two-stage methods for mildly nonlinear systems

1999 ◽  
Vol 82 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Zhong-Zhi Bai ◽  
Violeta Migallón ◽  
José Penadés ◽  
Daniel B. Szyld
Keyword(s):  
Nonlinear Systems ◽  
Two Stage

Identification of Nonlinear Systems Structured by Wiener-Hammerstein Model

2016 ◽  
Vol 6 (1) ◽  
pp. 167 ◽  
Author(s):  
A Brouri ◽  
S Slassi
Keyword(s):  
Nonlinear Systems ◽  
Identification Problem ◽  
Hammerstein Model ◽  
Asymptotically Stable ◽  
Two Stage ◽  
Series Connection ◽  
Static Nonlinearity ◽  
Identification Method ◽  
Frequency Identification ◽  
Nonlinear Static

Wiener-Hammerstein systems consist of a series connection including a nonlinear static element sandwiched with two linear subsystems. The problem of identifying Wiener-Hammerstein models is addressed in the presence of hard nonlinearity and two linear subsystems of structure entirely unknown (asymptotically stable). Furthermore, the static nonlinearity is not required to be invertible. Given the system nonparametric nature, the identification problem is presently dealt with by developing a two-stage frequency identification method, involving simple inputs.

scholarly journals An Efficient Iterative Method Based on Two-Stage Splitting Methods to Solve Weakly Nonlinear Systems

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 815 ◽  
Author(s):  
Abdolreza Amiri ◽  
Mohammad Taghi Darvishi ◽  
Alicia Cordero ◽  
Juan Ramón Torregrosa
Keyword(s):  
Nonlinear Systems ◽  
Iterative Method ◽  
Convergence Theorem ◽  
Splitting Method ◽  
Accurate Solution ◽  
Splitting Methods ◽  
Two Stage ◽  
Weakly Nonlinear ◽  
Cpu Time ◽  
Sparse Systems

In this paper, an iterative method for solving large, sparse systems of weakly nonlinear equations is presented. This method is based on Hermitian/skew-Hermitian splitting (HSS) scheme. Under suitable assumptions, we establish the convergence theorem for this method. In addition, it is shown that any faster and less time-consuming two-stage splitting method that satisfies the convergence theorem can be replaced instead of the HSS inner iterations. Numerical results, such as CPU time, show the robustness of our new method. This method is easy, fast and convenient with an accurate solution.

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