Title :
Global Exponential Stability of Fuzzy Cellular Neural Networks with Mixed Delays
Author :
Wu, Ranchao ; Chen, Liping
Author_Institution :
Sch. of Math., Anhui Univ., Hefei
Abstract :
In this paper, a class of fuzzy cellular neural networks with mixed delays is studied. By using the fixed point theorem, M-matrix theory and some analytic techniques, sufficient conditions for the existence and global exponential stability of the unique equilibrium point are obtained. For illustration, an example is given to show the effectiveness of the obtained results.
Keywords :
asymptotic stability; cellular neural nets; delays; fuzzy neural nets; matrix algebra; M-matrix theory; fixed point theorem; fuzzy cellular neural network; global exponential stability; mixed delay; Cellular neural networks; Delay; Feeds; Fuzzy logic; Fuzzy neural networks; Mathematics; Neurofeedback; Stability analysis; State feedback; Sufficient conditions;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.707
