Title :
A note on stability of analog neural networks with time delays
Author :
Cao, Y.J. ; Wu, Q.H.
Author_Institution :
Dept. of Electr. Eng. & Electron., Liverpool Univ., UK
fDate :
11/1/1996 12:00:00 AM
Abstract :
This note presents a generalized sufficient condition which guarantees stability of analog neural networks with time delays. The condition is derived using a Lyapunov functional and the stability criterion is stated as: the equilibrium of analog neural networks with delays is globally asymptotically stable if the product of the norm of connection matrix and the maximum neuronal gain is less than one
Keywords :
Lyapunov methods; analogue processing circuits; asymptotic stability; circuit stability; delays; dynamics; neural nets; stability criteria; Lyapunov function; asymptotic stability; connection matrix; equilibrium; neural dynamics; neuronal gain; stability criterion; sufficient condition; time delays; Artificial neural networks; Delay effects; Eigenvalues and eigenfunctions; Equations; Neural network hardware; Neural networks; Neurons; Stability; Sufficient conditions; Very large scale integration;
Journal_Title :
Neural Networks, IEEE Transactions on
