Semirecursive nonparametric algorithms for Hammerstein systems with stochastic autocorrelated input

被引：1
|
作者：
Chung, Ly-Inn [1 ]
Lin, Tsair-Chuan [1 ]
Wang, Chun-Chao [1 ]
机构：
[1] Natl Taipei Univ, Dept Stat, New Taipei, Taiwan
来源：
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE | 2022年 / 53卷 / 07期
关键词：
Semirecursive; nonlinearity; asymptotic unbiasedness; consistency; two-stage optimisation; ARX; IDENTIFICATION;
D O I：
10.1080/00207721.2021.2010833
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A Hammerstein system comprises a nonlinear static subsystem and a linear dynamic subsystem. Herein, semirecursive nonparametric estimators are proposed for the nonlinear static subsystem, and its asymptotic unbiasedness and consistency properties are demonstrated. The estimators are competitive in terms of computational cost and data storage capacity. The performance of the proposed algorithms was examined through both Monte Carlo simulation and application to empirical data.
引用
收藏
页码：1503 / 1515
页数：13
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