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Robust exponential stability of interval Cohen-Grossberg neural networks with time-varying delays. (English) Zbl 1198.34151

Summary: The problem of robust exponential stability for a class of interval Cohen-Grossberg neural networks with time-varying delays is investigated. Without assuming the boundedness and differentiability of the activation functions and any symmetry of interconnection matrices, some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point are derived. Some comparisons between the results presented in this paper and the previous results admit that our results are the improvement and extension of the existed ones. The validity and performance of the new results are further illustrated by two simulation examples.

Editorial remark: There are doubts about a proper peer-reviewing procedure of this journal. The editor-in-chief has retired, but, according to a statement of the publisher, articles accepted under his guidance are published without additional control.

MSC:
34K20Stability theory of functional-differential equations
92B20General theory of neural networks (mathematical biology)
93D09Robust stability of control systems