Stability Analysis for a Class of Stochastic Fuzzy Cellular Neural Networks with Markovian Jumping and Mixed Time Delays

Title:Stability Analysis for a Class of Stochastic Fuzzy Cellular Neural Networks with Markovian Jumping and Mixed Time Delays

Volume: 3 Issue: 1

Author(s): Jingyi Wang and Guoqiang Peng

Affiliation:

Keywords: Distributed time delays, exponential stability, fuzzy systems, Markovian jumping parameters, stochastic neural networks, time-varying delays.

Abstract: This paper focuses on solving the problem of checking the exponential stability of a class of stochastic fuzzy cellular neural networks with Markovian jumping parameters, time-varying delays and distributed delays. By constructing suitable Lyapunov functional and applying stochastic analysis, we firstly developed some sufficient conditions to guarantee the almost surely exponential stability and the exponential stability in the mean square of this kind of neural networks. We then showed, by developing several corollaries, that our results could be specialized to various cases including some published studies. Finally, a numerical example proves the effectiveness of our method.

Cite this article as:

Wang Jingyi and Peng Guoqiang, Stability Analysis for a Class of Stochastic Fuzzy Cellular Neural Networks with Markovian Jumping and Mixed Time Delays, Recent Advances in Communications and Networking Technology (Discontinued) 2014; 3 (1) . https://dx.doi.org/10.2174/2215081102666140620224251