Modified stochastic gradient identification algorithms with fast convergence rates-Reference-Cited by-同舟云学术

Modified stochastic gradient identification algorithms with fast convergence rates

Published:2010-11-08 Issue:9 Volume:17 Page:1281-1286
ISSN:1077-5463
Container-title:Journal of Vibration and Control
language:en
Short-container-title:Journal of Vibration and Control

Author:

Jing Chen ¹,Feng Ding ²

Affiliation:

1. Wuxi Professional College of Science and Technology, People's Republic of China, School of Communication and Control Engineering, Jiangnan University, People's Republic of China

2. School of Communication and Control Engineering, Jiangnan University, People's Republic of China,

Abstract

The stochastic gradient identification algorithm has slow convergence rates. This paper presents a modified stochastic gradient algorithm by introducing a convergence index in order to improve the convergence rate of the parameter estimation. The parameter estimation accuracy can be enhanced by choosing the convergence index and a numerical example shows that the proposed method is efficient.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science

Link

http://journals.sagepub.com/doi/pdf/10.1177/1077546310376989

Reference27 articles.

1. Performance bounds of forgetting factor least-squares algorithms for time-varying systems with finite measurement data

2. Performance analysis of multi-innovation gradient type identification methods

3. Time series AR modeling with missing observations based on the polynomial transformation

4. Auxiliary model based multi-innovation extended stochastic gradient parameter estimation with colored measurement noises

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