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Global exponential stability of impulsive Cohen-Grossberg neural network with time-varying delays. (English) Zbl 1142.34046

Summary: An impulsive Cohen-Grossberg neural network model with time-varying delays is considered. Applying the ideas of vector Lyapunov function, \(M\)-matrix theory and inequality technique, several new sufficient conditions are obtained to ensure global exponential stability of the equilibrium point for impulsive Cohen-Grossberg neural network with time-varying delays. These results generalize a few previous known results and remove some restrictions on the neural network. An example is given to show the effectiveness of the obtained results.

MSC:

34K20 Stability theory of functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
34K45 Functional-differential equations with impulses
34K60 Qualitative investigation and simulation of models involving functional-differential equations
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