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Mean square exponential stability of stochastic recurrent neural networks with time-varying delays. (English) Zbl 1152.60346
Summary: The stability of a class of stochastic Recurrent Neural Networks with time-varying delays is investigated in this paper. With the help of the Lyapunov function and the Dini derivative of the expectation of $V\left(t,X\left(t\right)\right)$ “along” the solution $X\left(t\right)$ of the model, a set of novel sufficient conditions on mean square exponential stability has been established. An example is also given to illustrate the effectiveness of our results.
##### MSC:
 60K20 Applications of Markov renewal processes 62M45 Neural nets and related approaches (inference from stochastic processes)
##### Keywords:
stochastic; neural network; delay; mean; stability
##### References:
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