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In this paper,a novel and effective approach to impulsive synchronization analysis excited by parameter white-noise of neural networks is investigated using the nonlinear operator named the generalized Dahlquist constant.The proposed approach offers a design procedure for impulsive synchronization of a large class of neural networks.Numerical simulations,where the theoretical results are applied to typical neural networks with and without delayed item,demonstrate the effectiveness and feasibility of the proposed technique.
In this paper, a novel and effective approach to impulsive synchronization analysis excited by parameter white-noise of neural networks is investigated using the nonlinear operator named the generalized Dahlquist constant. The proposed approach provides a design procedure for impulsive synchronization of a large class of neural networks. Numerical simulations, where the theoretical results are applied to typical neural networks with and without delayed item, demonstrate the effectiveness and feasibility of the proposed technique.