Title :
New results concerning exponential stability of delayed neural networks with impulses
Author_Institution :
Dept. of Math., Huaiyin Normal Univ., Huaiyin, China
Abstract :
Employing matrix measure approach and Lyapunov functional, the author studies global exponential stability of delayed neural networks with impulses in this paper. Some novel and sufficient conditions are given to guarantee the global exponential stability of the equilibrium point for such delayed neural networks with impulses. Finally, two numerical examples are provided to illustrate our theorems.
Keywords :
Lyapunov methods; asymptotic stability; delays; matrix algebra; neural nets; Lyapunov functional; delayed neural networks; global exponential stability; matrix measurement approach; network impulses; Artificial neural networks; Asymptotic stability; Cellular neural networks; Circuit stability; Delay; Stability criteria;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583324
