Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/83547
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Type: Journal article
Title: Novel robust stability criteria for stochastic Hopfield neural networks with time delays
Author: Yang, R.
Gao, H.
Shi, P.
Citation: IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2009; 39(2):467-474
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2009
ISSN: 1083-4419
1941-0492
Statement of
Responsibility: 
Rongni Yang, Huijun Gao, and Peng Shi
Abstract: In this paper, the problem of asymptotic stability for stochastic Hopfield neural networks (HNNs) with time delays is investigated. New delay-dependent stability criteria are presented by constructing a novel Lyapunov-Krasovskii functional. Moreover, the results are further extended to the delayed stochastic HNNs with parameter uncertainties. The main idea is based on the delay partitioning technique, which differs greatly from most existing results and reduces conservatism. Numerical examples are provided to illustrate the effectiveness and less conservativeness of the developed techniques.
Rights: © 2008 IEEE
RMID: 0020128170
DOI: 10.1109/TSMCB.2008.2006860
Appears in Collections:Electrical and Electronic Engineering publications

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