Title :
An improved global stability result for delayed cellular neural networks
Author_Institution :
Dept. of Electron., Istanbul Univ., Turkey
fDate :
8/1/2002 12:00:00 AM
Abstract :
This paper presents a sufficient condition for the uniqueness and global asymptotic stability of the equilibrium point for delayed cellular neural networks. This result improves and generalizes some of the previous stability results derived in the literature.
Keywords :
asymptotic stability; cellular neural nets; delays; optimisation; activation functions; asymptotic stability; delayed cellular neural networks; equilibrium point; improved global stability; mathematical model; positive diagonal matrix; time derivative; uniqueness; Asymptotic stability; Cellular neural networks; Circuits; Equations; Mathematical model; Stability analysis; Sufficient conditions;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2002.801264
