Maximum likelihood gradient-based iterative estimation algorithm for a class of input nonlinear controlled autoregressive ARMA systems

被引：0
|
作者：
Feiyan Chen
Feng Ding
Junhong Li
机构：
[1] Jiangnan University,Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education)
[2] Nantong University,School of Electrical Engineering
来源：
Nonlinear Dynamics | 2015年 / 79卷
关键词：
Parameter estimation; Maximum likelihood; Stochastic gradient; Simulation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper considers the parameter estimation problem for an input nonlinear controlled autoregressive ARMA model. The basic idea is to combine the maximum likelihood principle and the gradient search and to present a maximum likelihood gradient-based iterative estimation algorithm. The analysis and simulation results show that the proposed algorithm can effectively estimate the parameters of the input nonlinear controlled autoregressive ARMA systems.
引用
收藏
页码：927 / 936
页数：9
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