Title :
Exponential Stability of Fuzzy Cellular Neural Networks with Time-Varying Delays and Impulses
Author :
Liang, Jinming ; Li, Kelin
Author_Institution :
Sch. of Comput. Sci., Sichuan Univ. of Sci. & Eng., Zigong, China
fDate :
March 31 2009-April 2 2009
Abstract :
In this paper, a generalized model of fuzzy cellular neural networks (FCNNs) with time-varying delays and impulses is formulated and investigated. By employing the delay differential inequality with impulses initial conditions and the M-matrix theory, some new sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for FCNNs with time-varying delays and impulses are obtained. In particular, a more precise estimate of exponential convergence rate is provided. An example is given to show the effectiveness of the obtained results.
Keywords :
asymptotic stability; cellular neural nets; convergence; delay-differential systems; fuzzy neural nets; matrix algebra; time-varying systems; delay differential inequality; exponential convergence; exponential stability; generalized fuzzy cellular neural network model; m-matrix theory; time-varying delays; time-varying impulse; Artificial neural networks; Cellular neural networks; Computer science; Delay effects; Fuzzy logic; Fuzzy neural networks; Image processing; Recurrent neural networks; Stability; Sufficient conditions;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.724
