Title :
Exponential stability of periodic solutions for cellular neural networks with S-type distributed delays
Author_Institution :
Coll. of Inf. Sci. & Technol., Qingdao Univ. of Sci. & Technol., Qingdao
Abstract :
In this paper, cellular neural networks with variable coefficients and S-type distributed delays are considered. Sufficient conditions for the existence and exponential stability of the periodic solutions are established by using the coincidence degree theorem and differential inequality technique.
Keywords :
asymptotic stability; cellular neural nets; delays; S-type distributed delays; cellular neural networks; coincidence degree theorem; differential inequality technique; exponential stability; periodic solutions; Cellular neural networks; Stability; Cellular neural networks; Coincidence degree theory; Distributed delays; Exponential stability;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597856
