Robust Synchronization Criterion for Coupled Stochastic Discrete-Time Neural Networks with Interval Time-Varying Delays, Leakage Delay, and Parameter Uncertainties | Zendy

Myeongjin Park | Zendy; OhMin Kwon | Zendy; Ju H. Park | Zendy; Sangmoon Lee | Zendy; E. J. | Zendy

Open Access

Robust Synchronization Criterion for Coupled Stochastic Discrete-Time Neural Networks with Interval Time-Varying Delays, Leakage Delay, and Parameter Uncertainties

Author(s) -

Myeongjin Park,

OhMin Kwon,

Ju H. Park,

Sangmoon Lee,

E. J.

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/814692

Subject(s) - mathematics , lemma (botany) , control theory (sociology) , interval (graph theory) , weighting , synchronization (alternating current) , discrete time and continuous time , artificial neural network , computer science , topology (electrical circuits) , statistics , medicine , ecology , poaceae , control (management) , radiology , combinatorics , artificial intelligence , machine learning , biology

The purpose of this paper is to investigate a delay-dependent robust synchronization analysis for coupled stochastic discrete-time neural networks with interval time-varying delays in networks coupling, a time delay in leakage term, and parameter uncertainties. Based on the Lyapunov method, a new delay-dependent criterion for the synchronization of the networks is derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii’s functional and utilizing Finsler’s lemma without free-weighting matrices. Two numerical examples are given to illustrate the effectiveness of the proposed methods

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