Letters: Stability analysis of stochastic neural networks with Markovian jump parameters using delay-partitioning approach

Authors:
Weimin Chen;Qian Ma;Guoying Miao;Yijun Zhang
Affiliations:
Department of Applied Mathematics, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, PR China and School of Automation, Nanjing University of Science and Technology, Nanjing 2 ...;School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, PR China;School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, PR China;School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, PR China
Venue:
Neurocomputing
Year:
2013

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Abstract

In this paper, the problem of mean square asymptotic stability of stochastic neural networks with Markovian jumping parameters is considered. By choosing an augmented Lyapunov-Krasovskii functional and utilizing the delay-partitioning method, novel delay-dependent mean square asymptotic stability conditions are derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed approach.