Title :
Convergence behavior of high-order fuzzy cellular neural networks with time-varying delays
Author :
Shuping Xu ; Manchun Tan ; Huimin Liao
Author_Institution :
Dept. of Math., Jinan Univ., Guangzhou, China
Abstract :
In this paper, the convergence behaviors are considered for a class of high-order fuzzy cellular neural networks with time-varying delays.Some sufficient conditions are established to ensure that all solutions of the networks converge to zero point. Compared with some earlier works, the new criteria do not require the Lipschitz continuous condition on activation functions and the differentiability of variable delays. Finally, an example with numerical simulation is given to show the effectiveness of the proposed method and results.
Keywords :
cellular neural nets; delays; fuzzy neural nets; time-varying systems; transfer functions; Lipschitz continuous condition; activation functions; convergence behavior; high-order fuzzy cellular neural networks; time-varying delays; Asymptotic stability; Cellular neural networks; Control theory; Delay effects; Delays; Stability; Convergence; Delays; High-order neural networks; Time-varying coefficients;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561356
