Global exponential stability of memristive neural networks with impulse time window and time-varying delays

A generalized model of memristive neural networks with time-varying delays and impulse time window is considered. By utilizing Lyapunov stability theory, we establish several sufficient conditions for global exponential stability and formulate a relationship between the exponential convergence rate and the impulse parameters including window position, window radius as well as impulse strength. Numerical example is also presented to verify the effectiveness of the theoretical results.

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