Title :
An improved global asymptotic stability criterion for delayed cellular neural networks
Author :
He, Yong ; Wu, Min ; She, Jin-hua
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Abstract :
A new Lyapunov-Krasovskii functional is constructed for delayed cellular neural networks, and the S-procedure is employed to handle the nonlinearities. An improved global asymptotic stability criterion is also derived that is a generalization of, and an improvement over, previous results. Numerical examples demonstrate the effectiveness of the criterion.
Keywords :
asymptotic stability; linear matrix inequalities; neural nets; stability criteria; Lyapunov-Krasovskii functional; delayed cellular neural networks; global asymptotic stability criterion; linear matrix inequalities; Asymptotic stability; Cellular networks; Cellular neural networks; Delay; Educational programs; Helium; Linear matrix inequalities; Neural networks; Neurons; Output feedback; Delayed cellular neural networks; S-procedure; global asymptotic stability; linear matrix inequality (LMI); Algorithms; Artificial Intelligence; Computer Simulation; Image Processing, Computer-Assisted; Pattern Recognition, Automated; Principal Component Analysis;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2005.860874
