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New stability criteria for neutral-type Cohen–Grossberg neural networks with discrete and distributed delays. (English) Zbl 1255.93111
Summary: This paper studies the existence, uniqueness and globally robust exponential stability for a class of uncertain neutral-type Cohen–Grossberg neural networks with time-varying and unbounded distributed delays. Based on a Lyapunov–Krasovskii functional, by involving a free-weighting matrix, using the homeomorphism mapping principle, Cauchy–Schwarz inequality, Jensen integral inequality, linear matrix inequality techniques and matrix decomposition method, several delay-dependent and delay-independent sufficient conditions are obtained for the robust exponential stability of the considered neural networks. Two numerical examples are given to show the effectiveness of our results.

MSC:
93D09 Robust stability
93D30 Lyapunov and storage functions
93B28 Operator-theoretic methods
92B20 Neural networks for/in biological studies, artificial life and related topics
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