Title :
Exponential stability of almost periodic solutions for cellular networks with S-type distributed delays
Author_Institution :
Coll. of Inf. Sci. & Technol., Qingdao Univ. of Sci. & Technol., Qingdao
Abstract :
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; variable coefficients; Cellular neural networks; Educational institutions; Electronic mail; Image processing; Information science; Land mobile radio cellular systems; Pattern recognition; Signal processing; Stability; Sufficient conditions; Cellular neural networks; Coincidence degree theory; Exponential stability; Periodic solution;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605621
