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Exponential synchronization of a class of chaotic neural networks. (English) Zbl 1060.93519
Summary: This paper deals with the synchronization problem of a class of chaotic neural networks with or without delays. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks with or without delays. Using the drive-response concept, a control law is derived to achieve the state synchronization of two identical chaotic neural networks. Furthermore, based on the Lyapunov stability method and the Halanay inequality lemma, a delay independent sufficient exponential synchronization condition is derived. The synchronization condition is easy to verify and relies on the connection matrix in the driven networks and the suitable designed controller gain matrix in the response networks. Finally, some illustrative examples are given to demonstrate the effectiveness of the presented synchronization scheme.

MSC:
93C10 Nonlinear systems in control theory
34K23 Complex (chaotic) behavior of solutions to functional-differential equations
37D45 Strange attractors, chaotic dynamics of systems with hyperbolic behavior
37N25 Dynamical systems in biology
92B20 Neural networks for/in biological studies, artificial life and related topics
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