期刊
NEUROCOMPUTING
卷 127, 期 -, 页码 144-151出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2013.08.028
关键词
Cohen-Grossberg BAM neural networks; Exponential stability; Linear matrix inequality; Stochastic effect; Time-varying delays
资金
- National Basic Research Program of China [2010CB732501]
- National Natural Science Foundation of China [61273015]
This paper considers the issue of exponential stability analysis for stochastic Cohen-Grossberg BAM (SCGBAM) neural networks with discrete and distributed time-varying delays. The exponential stability criteria are proposed by applying stochastic analysis theory and establishing a new Lyapunov-Krasovskii functional. A set of novel sufficient conditions is obtained to guarantee the exponential stability of stochastic Cohen-Grossberg BAM neural networks with discrete and distributed time-varying delays. The several exponential stability criteria proposed in this paper are simpler and effective. Finally, two numerical examples are provided to demonstrate the low conservatism and effectiveness of the proposed results. (C) 2013 Elsevier B.V. All rights reserved.
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