Title :
Robust stability for interval Hopfield neural networks with time delay
Author :
Liao, Xiaofeng ; Yu, Juebang
Author_Institution :
Dept. of Optoelectron. Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fDate :
9/1/1998 12:00:00 AM
Abstract :
The conventional Hopfield neural network with time delay is intervalized to consider the bounded effect of deviation of network parameters and perturbations yielding a novel interval dynamic Hopfield neural network (IDHNN) model. A sufficient condition related to the existence of unique equilibrium point and its robust stability is derived
Keywords :
Hopfield neural nets; delays; stability; IDHNN model; interval dynamic Hopfield neural network; network parameter deviation; network perturbations; robust stability; time delay; unique equilibrium point; Artificial neural networks; Delay effects; Delay estimation; Hopfield neural networks; Integrated circuit interconnections; Magnesium compounds; Neural networks; Neurons; Robust stability; Sufficient conditions;
Journal_Title :
Neural Networks, IEEE Transactions on
