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Novel conditions on exponential stability of a class of delayed neural networks with state-dependent switching
1College of Mathematics and statistics, South-Central University For Nationalities, Wuhan 430074, China.
Abstract:
This paper is concerned with the global exponential stability on a class of delayed neural networks with state-dependent switching. Under the novel conditions, some sufficient criteria ensuring exponential stability of the proposed system are obtained. In particular, the obtained conditions complement and improve earlier publications on conventional neural networks with continuous or discontinuous right-hand side. Numerical simulations are also presented to illustrate the effectiveness of the obtained results.
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