Exponential Stability of a Class of High-Order Hybrid Neural Networks
This paper considers a generalized model of high-order hybrid neural networks with time-varying delays and impulsive effects is considered. By establishing an impulsive delay differential inequality and using the method of Lyapunov functions, we investigate the global exponential stability of high-order dynamical neural networks with time-varying delays and impulsive effects. Our sufficient conditions ensuring the stability are dependent on delays and impulses and show delay and impulsive effects on the stability of neural networks.
KeywordsExponential stability high-order hybrid neural networks Lyapunov function impulse effects
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