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

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.