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Robust exponential stability for interval neural networks with delays and non-Lipschitz activation functions. (English) Zbl 1242.93113

Summary: In this paper, the global robust exponential stability of interval neural networks with delays and inverse Hölder neuron activation functions is considered. By using Linear Matrix Inequality (LMI) techniques and Brouwer degree properties, the existence and uniqueness of the equilibrium point are proved. By applying the Lyapunov functional approach, a sufficient condition which ensures that the network is globally robustly exponentially stable is established. A numerical example is provided to demonstrate the validity of the theoretical results.

MSC:

93D09 Robust stability
92B20 Neural networks for/in biological studies, artificial life and related topics
34H05 Control problems involving ordinary differential equations
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