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2014 Exponential Synchronization for Stochastic Neural Networks with Mixed Time Delays and Markovian Jump Parameters via Sampled Data
Yingwei Li, Xueqing Guo
Abstr. Appl. Anal. 2014: 1-17 (2014). DOI: 10.1155/2014/505164

Abstract

The exponential synchronization issue for stochastic neural networks (SNNs) with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI) approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

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Yingwei Li. Xueqing Guo. "Exponential Synchronization for Stochastic Neural Networks with Mixed Time Delays and Markovian Jump Parameters via Sampled Data." Abstr. Appl. Anal. 2014 1 - 17, 2014. https://doi.org/10.1155/2014/505164

Information

Published: 2014
First available in Project Euclid: 2 October 2014

zbMATH: 07022504
MathSciNet: MR3178871
Digital Object Identifier: 10.1155/2014/505164

Rights: Copyright © 2014 Hindawi

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