Title :
Exponential p -stability of Cohen-Grossberg neural networks with time-delays and impulses
Author :
Qin Fajin ; Yao Xiaojie
Author_Institution :
Dept. of Math. & Comput. Sci., Liuzhou Teachers Coll., Liuzhou, China
Abstract :
In this paper , we consider a class of Cohen-Grossberg neural networks with time-delays and impulses. By using the properties of M -cone and differential inequality technique, criteria on the exponential p -stability of this model are derived, and the estimated exponential convergence rate is also obtained. The results of this paper are new and they supplement previously known results.
Keywords :
asymptotic stability; delays; differential equations; neural nets; Cohen-Grossberg neural networks; differential inequality technique; exponential convergence rate; exponential p-stability; impulses; m-cone property; time-delays; Artificial neural networks; Asymptotic stability; Biological neural networks; Convergence; Delay; Differential equations; Stability analysis; Cohen-Grossberg Neural Networks; Exponential p -stability; Time-delays;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
