Global Exponential Stability of Hopfield-type Neural Networks with Time Delays
نویسنده
چکیده
The paper is concerned with the improvement of sufficient conditions for the exponential stability of Hopfield-type neural networks displaying interaction delays. The results are based on a method obtained in our previous work that combines an idea suggested by Malkin for studying the absolute stability of a nonlinear system via their linearisations and a procedure proposed by Kharitonov for construction of an “exact” Liapunov-Krasovskii functional used in the analysis of uncertain linear time delay systems. Since the Liapunov function method give only sufficient conditions for stability, the improvement of these criteria is obviously necessary. These less conservative conditions are suitable for the implementation of recurrent neural networks.
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