Abstract
In this paper, the hybrid function projective synchronization of unknown Cohen-Grossberg neural networks with time delays and noise perturbation is investigated. A hybrid control scheme combining open-loop control and adaptive feedback control is designed to guarantee that the drive and response networks can be synchronized up to a scaling function matrix with parameter identification by utilizing the LaSalle-type invariance principle for stochastic differential equations. Finally, the corresponding numerical simulations are carried out to demonstrate the validity of the presented synchronization method.
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