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Exponential \(p\)-stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays. (English) Zbl 1165.34043

Summary: We study impulsive stochastic Cohen-Grossberg neural networks with mixed delays. By establishing an \(L\)-operator differential inequality with mixed delays and using the properties of \(M\)-cone and stochastic analytic technique, we obtain some sufficient conditions ensuring the exponential \(p\)-stability of the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. These results generalize a few previous known results and remove some restrictions on the neural networks. Two examples are also discussed to illustrate the efficiency of the obtained results.

MSC:

34K20 Stability theory of functional-differential equations
34K45 Functional-differential equations with impulses
35K50 Systems of parabolic equations, boundary value problems (MSC2000)
92B20 Neural networks for/in biological studies, artificial life and related topics
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