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Synchronization of coupled neural networks with random coupling strengths and mixed probabilistic time‐varying delays
Author(s) -
Yang Xinsong,
Cao Jinde,
Lu Jianquan
Publication year - 2013
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.2868
Subject(s) - synchronization (alternating current) , probabilistic logic , coupling (piping) , interval (graph theory) , matlab , control theory (sociology) , computer science , artificial neural network , basis (linear algebra) , lyapunov function , mathematics , topology (electrical circuits) , nonlinear system , engineering , artificial intelligence , mechanical engineering , physics , geometry , control (management) , combinatorics , quantum mechanics , operating system
SUMMARY This paper investigates the global asymptotic synchronization in an array of coupled neural networks with random coupling strengths, probabilistic interval time‐varying coupling delays as well as unbounded distributed delays (mixed delays). Two important integral inequalities that include the Jensen's inequality as a special case are developed. On the basis of the developed inequalities, the properties of random variables and Lyapunov functional method, several delay‐dependent sufficient synchronization criteria are derived for the considered model. The derived synchronization criteria are formulated by linear matrix inequalities (LMIs) and can be easily verified by using MATLAB LMI Toolbox. Some existing results are improved and extended by taking different values of parameters of the obtained results. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results. Copyright © 2012 John Wiley & Sons, Ltd.