Dissipativity analysis of stochastic neural networks with time delays. (English) Zbl 1267.93164
Summary: This paper is concerned with the dissipativity problem of stochastic neural networks with time delay. A new stochastic integral inequality is first proposed. By utilizing the delay partitioning technique combined with the stochastic integral inequalities, some sufficient conditions ensuring mean-square exponential stability and dissipativity are derived. Some special cases are also considered. All the given results in this paper are not only dependent upon the time delay, but also upon the number of delay partitions. Finally, some numerical examples are provided to illustrate the effectiveness and improvement of the proposed criteria.
MSC:
| 93E03 | Stochastic systems in control theory (general) |
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 34K20 | Stability theory of functional-differential equations |
Keywords:
neural networks; stochastic systems; time delays; exponential stability; dissipativity analysisReferences:
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