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Synchronization of chaotic delayed neural networks via impulsive control. (English) Zbl 1406.34080

Summary: This paper is concerned with the impulsive synchronization problem of chaotic delayed neural networks. By employing Lyapunov stability theorem, impulsive control theory and linear matrix inequality (LMI) technique, several new sufficient conditions ensuring the asymptotically synchronization for coupled chaotic delayed neural networks are derived. Based on these new sufficient conditions, an impulsive controller is designed. Moreover, the stable impulsive interval of synchronized neural networks is objectively estimated by combining the MATLAB LMI toolbox and one of the two given equations. Two examples with numerical simulations are given to illustrate the effectiveness of the proposed method.

MSC:

34D06 Synchronization of solutions to ordinary differential equations
34C60 Qualitative investigation and simulation of ordinary differential equation models
34K45 Functional-differential equations with impulses
34C28 Complex behavior and chaotic systems of ordinary differential equations
34H05 Control problems involving ordinary differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics

Software:

LMI toolbox; Matlab