Title :
An analysis of global asymptotic stability of delayed cellular neural networks
Author_Institution :
Dept. of Electron., Istanbul Univ., Turkey
fDate :
9/1/2002 12:00:00 AM
Abstract :
In this paper, a new sufficient condition is given for the uniqueness and global asymptotic stability of the equilibrium point for delayed cellular neural networks (DCNNs). This condition imposes constraints on the feedback and delayed feedback matrices of a DCNN independently of the delay parameter. This result is also compared with the previous results derived in the literature.
Keywords :
asymptotic stability; cellular neural nets; delays; matrix algebra; delay parameter; delayed cellular neural networks; delayed feedback matrices; equilibrium point; feedback; global asymptotic stability; Asymptotic stability; Cellular neural networks; Delay; Equations; Neural networks; Neurofeedback; Output feedback; Stability analysis; State feedback; Sufficient conditions;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2002.1031957
