Adaptive synchronization for competitive neural networks with different time scales and stochastic perturbation

Authors:
Haibo Gu
Affiliations:
College of Mathematics, Physics and Information Science, Xinjiang Normal University, Urumqi 830054, China
Venue:
Neurocomputing
Year:
2009

Citing 12
Cited 2

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Abstract

In this paper, an adaptive feedback controller is designed to achieve complete synchronization of coupled delayed competitive neural networks with different time scales and stochastic perturbation. LaSalle-type invariance principle for stochastic differential delay equations is employed to investigate the globally almost surely asymptotical stability of the error dynamical system. An example with numerical simulation is given to demonstrate the effectiveness of the theory results.