Title :
Delay-dependent exponential stability analysis of delayed cellular neural networks
Author :
Liao, Xiaofeng ; Yu, Juebang ; Chen, Guanrong
Author_Institution :
Dept. of Comput. Sci. & Eng., Chongqing Univ., China
fDate :
29 June-1 July 2002
Abstract :
For the delayed cellular neural networks, the estimate of exponential convergence rate and exponential stability is considered in this paper. The Lyapunov-Krasovskii functionals combined with linear matrix inequality (LMI) approach are employed to investigate the bound on the cell template and delay-type cell template matrices so that the systems are exponentially stable. Some criteria for the exponential stability which can give information on the delay-dependence are derived.
Keywords :
Lyapunov matrix equations; cellular neural nets; linear matrix inequalities; stability; Lyapunov-Krasovskii functionals; cell template; delay-dependent exponential stability analysis; delay-type cell template matrices; delayed cellular neural networks; exponential convergence rate; linear matrix inequality; Cellular neural networks; Computer science; Convergence; Delay effects; Delay estimation; Delay systems; Differential equations; Linear matrix inequalities; Stability analysis; Stability criteria;
Conference_Titel :
Communications, Circuits and Systems and West Sino Expositions, IEEE 2002 International Conference on
Print_ISBN :
0-7803-7547-5
DOI :
10.1109/ICCCAS.2002.1179095