Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/96623
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Type: Journal article
Title: Adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching parameters
Author: Zhou, W.
Zhu, Q.
Shi, P.
Su, H.
Fang, J.
Zhou, L.
Citation: IEEE Transactions on Cybernetics, 2014; 44(12):2848-2860
Publisher: IEEE
Issue Date: 2014
ISSN: 2168-2267
2168-2275
Statement of
Responsibility: 
Wuneng Zhou, Qingyu Zhu, Peng Shi, Hongye Su, Jian’an Fang, and Liuwei Zhou
Abstract: In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks of neutral-type with Markovian switching parameters. Using the M-matrix approach and the stochastic analysis method, some sufficient conditions are obtained to ensure three kinds of adaptive synchronization for the stochastic neutral-type neural networks. These three kinds of adaptive synchronization include the almost sure asymptotical synchronization, exponential synchronization in p th moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.
Keywords: Adaptive synchronization; M-matrix; Markovian switching; neutral-type neural network
Rights: © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
RMID: 0030017513
DOI: 10.1109/TCYB.2014.2317236
Grant ID: http://purl.org/au-research/grants/arc/DP140102180
Appears in Collections:Electrical and Electronic Engineering publications

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