DocumentCode
3338971
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
fYear
2010
fDate
23-25 June 2010
Firstpage
357
Lastpage
362
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICICIS.2010.5534804
Filename
5534804
Link To Document