Title :
Global stability conditions for delayed CNNs
Author_Institution :
Dept. of Appl. Math., Southeast Univ., Nanjing, China
fDate :
11/1/2001 12:00:00 AM
Abstract :
Based on the Lyapunov stability theorem as well as some facts about the positive definiteness and inequality of matrices, a new sufficient condition is presented for the existence of a unique equilibrium point and its global asymptotic stability for delayed CNNs. This condition imposes constraints on the feedback matrices independent of the delay parameter. This condition is less restrictive than that given in earlier references
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; feedback; matrix algebra; DCNNs; Lyapunov stability theorem; cellular neural networks; delay parameter; delayed CNNs; feedback matrices; global asymptotic stability; global stability conditions; matrix inequality; positive definiteness; sufficient condition; unique equilibrium point; Asymptotic stability; Cellular neural networks; Delay effects; Linear matrix inequalities; Lyapunov method; Neural networks; Neurofeedback; Output feedback; State feedback; Sufficient conditions;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
