Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/81858
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Type: Journal article
Title: Stochastic synchronization of Markovian jump neural networks with time-varying delay using sampled data
Author: Wu, Z.
Shi, P.
Su, H.
Chu, J.
Citation: IEEE Transactions on Cybernetics, 2013; 43(6):1796-1806
Publisher: IEEE
Issue Date: 2013
ISSN: 2168-2267
2168-2275
Statement of
Responsibility: 
Zheng-Guang Wu, Peng Shi, Hongye Su, and Jian Chu
Abstract: In this paper, the problem of sampled-data synchronization for Markovian jump neural networks with time-varying delay and variable samplings is considered. In the framework of the input delay approach and the linear matrix inequality technique, two delay-dependent criteria are derived to ensure the stochastic stability of the error systems, and thus, the master systems stochastically synchronize with the slave systems. The desired mode-independent controller is designed, which depends upon the maximum sampling interval. The effectiveness and potential of the obtained results is verified by two simulation examples.
Keywords: Models, Statistical; Markov Chains; Stochastic Processes; Sample Size; Algorithms; Neural Networks (Computer); Computer Simulation; Signal Processing, Computer-Assisted
Rights: © 2013 IEEE
RMID: 0020134116
DOI: 10.1109/TSMCB.2012.2230441
Appears in Collections:Electrical and Electronic Engineering publications

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