Title :
Periodicity of Cohen-Grossberg-type fuzzy neural networks with time-varying delays and impulses
Author :
Liang, Jinming ; Zhang, Xinhua
Author_Institution :
Sch. of Comput. Sci., Sichuan Univ. of Sci. & Eng., Zigong, China
Abstract :
In this paper, a class of Cohen-Grossberg-type fuzzy neural networks with time-varying delays and impulses is investigated. By employing differential inequality and M-matrix theory, some sufficient conditions ensuring the existence and global exponential stability of the periodic oscillatory solution for Cohen-Grossberg-type fuzzy neural networks with time-varying delays and impulses are obtained. An examples is given to show the effectiveness of the obtained results.
Keywords :
Artificial neural networks; Cellular neural networks; Delay effects; Fuzzy neural networks; Neurofeedback; Neurons; Recurrent neural networks; Stability; State feedback; Sufficient conditions; Cohen-Grossberg-type fuzzy neural networks; Periodic oscillatory solution; exponential stability; impulses; time-varying delays;
Conference_Titel :
Information Sciences and Interaction Sciences (ICIS), 2010 3rd International Conference on
Conference_Location :
Chengdu, China
Print_ISBN :
978-1-4244-7384-7
Electronic_ISBN :
978-1-4244-7386-1
DOI :
10.1109/ICICIS.2010.5534804
