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Adaptive lag synchronization in unknown stochastic chaotic neural networks with discrete and distributed time-varying delays. (English) Zbl 1221.82078

Summary: In this Letter, we have dealt with the problem of lag synchronization and parameter identification for a class of chaotic neural networks with stochastic perturbation, which involve both the discrete and distributed time-varying delays. By the adaptive feedback technique, several sufficient conditions have been derived to ensure the synchronization of stochastic chaotic neural networks. Moreover, all the connection weight matrices can be estimated while the lag synchronization is achieved in mean square at the same time. The corresponding simulation results are given to show the effectiveness of the proposed method.

MSC:

82C32 Neural nets applied to problems in time-dependent statistical mechanics
82C31 Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics
92B20 Neural networks for/in biological studies, artificial life and related topics
60K20 Applications of Markov renewal processes (reliability, queueing networks, etc.)
90B15 Stochastic network models in operations research
34B45 Boundary value problems on graphs and networks for ordinary differential equations
34C28 Complex behavior and chaotic systems of ordinary differential equations
34H10 Chaos control for problems involving ordinary differential equations
34D06 Synchronization of solutions to ordinary differential equations
93C10 Nonlinear systems in control theory
93B52 Feedback control
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