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Zbl 1240.93362
Zhang, Zifang; Xu, Daoyi
A note on stability of stochastic delay neural networks. (English)
[J] Chin. J. Eng. Math. 27, No. 4, 720-730 (2010). ISSN 1005-3085

Summary: The almost sure exponential stability for a stochastic recurrent neural network with time-varying delays is discussed by means of a nonnegative semi-martingale convergence theorem, the Lyapunov functional method and the characteristics of stochastic delay recurrent neural networks. New algebraic criteria of the almost sure exponential stability for the stochastic recurrent neural network with time-varying delays are derived. These algebraic criteria are simple and practical. Two examples show that these new algebraic criteria are better than the relative criteria for the stochastic Hopfield neural network.

MSC 2000:: *93E15 Stochastic stability
92B20 General theory of neural networks
93D20 Asymptotic stability of control systems

Keywords: stochastic recurrent neural networks; time-varying delays; almost sure exponential stability; sample Lyapunov exponent

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