Title :
Global robust stability of delayed neural networks
Author_Institution :
Dept. of Electr.-Electron. Eng., Istanbul Univ., Turkey
Abstract :
This work presents a sufficient condition for the existence, uniqueness, and global robust stability of the equilibrium point for Hopfield-type delayed neural networks. The result imposes constraint conditions on the boundary values of the network parameters independently of the delay parameter. This result is compared with the previous results derived in the literature.
Keywords :
Hopfield neural nets; delays; network parameters; stability; Hopfield-type neural networks; boundary values; constraint conditions; delay parameter; delayed neural networks; equilibrium analysis; equilibrium point; global robust stability; network parameters; Asymptotic stability; Delay effects; Equations; Hopfield neural networks; Neural networks; Neurons; Robust stability; Stability analysis; Sufficient conditions; Uncertainty;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2002.807515
