期刊
NEUROCOMPUTING
卷 149, 期 -, 页码 1280-1285出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2014.09.001
关键词
Discrete and distributed delays; Lyapunov functional; Linear matrix inequality; Markovian jumping parameters; Recurrent neural networks
资金
- NBHM [2/48(10)/2011-RD-II/865]
In this paper, global stability of Markovian jumping recurrent neural networks with discrete and distributed delays (MJRNN) is considered. A novel linear matrix inequality (LMI) based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of Markovian jumping recurrent neural networks with discrete and distributed delays. By applying Lyapunov method and some inequality techniques, several sufficient conditions are obtained under which the delayed neural networks are stable. Finally, numerical examples are given to demonstrate the correctness of the theoretical results. (c) 2014 Elsevier B.V. All rights reserved.
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