Modern Applied Science
Global Exponential Stability of a Class of Neural Networks with Finite Distributed Delays
Abstract
In this paper, global exponential stability of a class of neural networks with finite distributed delays is investigated by
matrix measure technique and Halanay inequality. Several sufficient conditions are given to guarantee global
exponential stability of the neural networks without assuming the differentiability of delay. At last, two examples are
given to illustrate the applicability of our results.
matrix measure technique and Halanay inequality. Several sufficient conditions are given to guarantee global
exponential stability of the neural networks without assuming the differentiability of delay. At last, two examples are
given to illustrate the applicability of our results.
This work is licensed under a Creative Commons Attribution 3.0 License.
Modern Applied Science ISSN 1913-1844 (Print) ISSN 1913-1852 (Online)
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