Delay-dependent asymptotic stability for stochastic delayed recurrent neural networks with time varying delays. (English) Zbl 1144.34375

Summary: The global asymptotic stability of stochastic recurrent neural networks with time varying delays is analyzed. By utilizing a Lyapunov functional and combining it with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of stochastic delayed recurrent neural networks. In addition, an example is provided to illustrate the applicability of the result.


34K20 Stability theory of functional-differential equations
34K50 Stochastic functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
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