Global synchronization of coupled delayed neural networks and applications to chaotic CNN models. (English) Zbl 1077.37506
Summary: This paper formulates the model and then studies its dynamics of a system of linearly and diffusively coupled identical delayed neural networks (DNNs), which is a generalization of delayed Hopfied neural networks (DHNNs) and delayed cellular neural networks (DCNNs). In particularly, a simple yet generic sufficient condition for global synchronization of such coupled DNNs is derived based on the Lyapunov functional methods and Hermitian matrix theory. It is shown that global synchronization of coupled DNNs is ensured by a suitable design of the coupling matrix and the inner linking matrix. Furthermore, the result is applied to some typical chaotic neural networks. Finally, numerical simulations are presented to demonstrate the effectiveness of the approach.
MSC:
| 37D45 | Strange attractors, chaotic dynamics of systems with hyperbolic behavior |
Keywords:
chaos; synchronization; delayed neural networks; chaotic cellular neural networks; Lyapunov functional methods; Hermitian matrix theory; numerical simulationsReferences:
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