Journal
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
Volume 29, Issue 2, Pages 331-348Publisher
SPRINGER BIRKHAUSER
DOI: 10.1007/s00034-009-9138-z
Keywords
Neural networks; Stochastic systems; Markovian jump parameters; Time-varying delays; LMIs
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Funding
- Natural Science Foundation of China [60674055, 60774047]
- Taishan Scholar Programme of Shandong Province
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This paper is concerned with the problem of delay-dependent mean square exponential stability for a class of delayed stochastic Hopfield neural networks with Markovian jump parameters. The delays here are time-varying delays. Based on a new Lyapunov-Krasovskii functional, delay-dependent stability conditions are derived by means of linear matrix inequalities (LMIs). It is shown that the proposed results can contain some existing stability conditions as a special case. Finally, three numerical examples are given to illustrate the effectiveness of the proposed method, and the simulations show that our results are less conservative than the existing ones.
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