期刊
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
卷 94, 期 7, 页码 1479-1500出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207160.2016.1190013
关键词
Dissipativity; linear matrix inequality; Lyapunov method; Markovian jump parameters; impulsive neural networks; 34A34; 34D23; 92B20; 34K36; 34K20
资金
- University Grants Commission - Basic Science Research (UGC - BSR), Govt. of India, New Delhi
This paper discusses the issue of dissipativity and passivity analysis for a class of impulsive neural networks with both Markovian jump parameters and mixed time delays. The jumping parameters are modelled as a continuous-time discrete-state Markov chain. Based on a multiple integral inequality technique, a novel delay-dependent dissipativity criterion is established via a suitable Lyapunov functional involving the multiple integral terms. The proposed dissipativity and passivity conditions for the impulsive neural networks are represented by means of linear matrix inequalities. Finally, three numerical examples are given to show the effectiveness of the proposed criteria.
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