Journal
NEUROCOMPUTING
Volume 72, Issue 7-9, Pages 1782-1788Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2008.05.006
Keywords
Discrete-time neural network; Stochastic neural networks; Time-varying delays; Passivity; Robust passivity
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Funding
- National Natural Science Foundation of China [10772152]
- Chongqing Municipal Education Commission [KJ070401]
- Royal Society of the UK and the National Natural Science Foundation of China
- Alexander von Humboldt Foundation of Germany
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In this paper. the problem of passivity analysis is investigated for a class of discrete-time stochastic neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, where the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By constructing proper Lyapunov-Krasovskii functional and employing a combination of the free-weighting matrix method and stochastic analysis technique, a delay-dependent passivity condition is derived in terms of linear matrix inequalities (LMIs). Furthermore, when the parameter uncertainties appear in the discrete-time stochastic neural networks with time-varying delays, a delay-dependent robust passivity condition is also presented. An example is given to show the effectiveness of the proposed criterion. (C) 2008 Elsevier B.V. All rights reserved.
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