An iterative numerical algorithm for modeling a class of Wiener nonlinear systems

This letter presents an iterative estimation algorithm for modeling a class of output nonlinear systems. The basic idea is to derive an estimation model and to solve an optimization problem using the gradient search. The proposed iterative numerical algorithm can estimate the parameters of a class o...

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Bibliographic Details
Published in:Applied mathematics letters Vol. 26; no. 4; pp. 487 - 493
Main Authors: Xiong, Weili, Ma, Junxia, Ding, Ruifeng
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.04.2013
Subjects:
Algorithms
Convergence
Dynamical systems
Gradient search
Iterative methods
Mathematical models
Nonlinear dynamics
Numerical algorithm
Numerical analysis
Optimization
Parameter estimation
System modeling
Wiener nonlinear system
System modeling
Gradient search
Parameter estimation
Wiener nonlinear system
Numerical algorithm
ISSN:0893-9659, 1873-5452
Online Access:Get full text
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Summary:This letter presents an iterative estimation algorithm for modeling a class of output nonlinear systems. The basic idea is to derive an estimation model and to solve an optimization problem using the gradient search. The proposed iterative numerical algorithm can estimate the parameters of a class of Wiener nonlinear systems from input–output measurement data. The proposed algorithm has faster convergence rates compared with the stochastic gradient algorithm. The numerical simulation results indicate that the proposed algorithm works well.
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ISSN:0893-9659
1873-5452
DOI:10.1016/j.aml.2012.12.001