Parameter identification of systems with preload nonlinearities based on the finite impulse response model and negative gradient search-Reference-Cited by-同舟云学术

Parameter identification of systems with preload nonlinearities based on the finite impulse response model and negative gradient search

Published:2012-11 Issue:5 Volume:219 Page:2498-2505
ISSN:0096-3003
Container-title:Applied Mathematics and Computation
language:en
Short-container-title:Applied Mathematics and Computation

Author:

Chen Jing,Lu Xianling,Ding Rui

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference79 articles.

1. Least squares based iterative identification for a class of multirate systems;Liu;Automatica,2010

2. Convergence of stochastic gradient algorithm for multivariable ARX-like systems;Liu;Computers and Mathematics with Applications,2010

3. Gradient based and least-squares based iterative identification methods for OE and OEMA systems;Ding;Digital Signal Processing,2010

4. Identification of Hammerstein output-error systems with two-segment nonlinearities: algorithm and applications;Yu;Journal of Control and Intelligent Systems,2010

5. Gradient based and least squares based iterative estimation algorithms for multi-input multi-output systems;Ding;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering,2012

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identification of switched FIR systems with random missing outputs: A variational Bayesian approach;Journal of the Franklin Institute;2021-01

2. Coupled stochastic gradient identification algorithms for multivariate output-error systems using the auxiliary model;International Journal of Control, Automation and Systems;2017-07-20

3. Multi-model recursive identification for nonlinear systems with non-uniformly sampling;Cluster Computing;2016-11-29

4. A proportional differential control method for a time-delay system using the Taylor expansion approximation;Applied Mathematics and Computation;2014-06

5. Parameter Identification Methods for an Additive Nonlinear System;Circuits, Systems, and Signal Processing;2014-04-16