Title :
Stability analysis of delayed neural networks
Author_Institution :
Dept. of Electron., Istanbul Univ., Turkey
fDate :
7/1/2000 12:00:00 AM
Abstract :
In this paper, the author derives several sufficient conditions for the asymptotic stability of delayed neural networks. These conditions ensure the asymptotic stability of the equilibrium point of a delayed neural network independently of the delay parameter. The results obtained impose constraint conditions on the interconnection matrix of the neural system. These results are also compared with the earlier results derived in the literature
Keywords :
Lyapunov methods; asymptotic stability; delays; matrix algebra; neural nets; asymptotic stability; constraint conditions; delayed neural networks; equilibrium point; interconnection matrix; stability analysis; sufficient conditions; Asymptotic stability; Bifurcation; Circuit stability; Damping; Neural networks; Power system analysis computing; Power system stability; Power system transients; Stability analysis; Transient analysis;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
