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Almost surely asymptotic synchronization for stochastic neural networks of neutral type with Markovian jumping parameters.

Authors :
Wu, Tao
Xiong, Lianglin
Cao, Jinde
Xie, Xueqin
Source :
International Journal of Adaptive Control & Signal Processing. Oct2019, Vol. 33 Issue 10, p1524-1551. 28p.
Publication Year :
2019

Abstract

Summary: This paper studies the problem of the almost surely asymptotic synchronization for a class of stochastic neural networks of neutral type with both Markovian jumping parameters and mixed time delays. Based on the stochastic analysis theory, LaSalle‐type invariance principle, and delayed state‐feedback control technique, some novel delay‐dependent sufficient criteria to guarantee the almost surely asymptotic synchronization are given. These criteria are expressed as the linear matrix inequalities, which can be easily checked by MATLAB LMI Control Toolbox. Finally, four numerical examples and their simulations are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08906327
Volume :
33
Issue :
10
Database :
Academic Search Index
Journal :
International Journal of Adaptive Control & Signal Processing
Publication Type :
Academic Journal
Accession number :
139114605
Full Text :
https://doi.org/10.1002/acs.3047