Title :
Stability conditions for bi-directional associative memory neural networks with delay
Author :
Zhou, Dongming ; Cao, Jinde
Author_Institution :
Inf. Coll., Yunnan Univ., Kunming, China
Abstract :
Bi-directional associative memory (BAM) models are two-layer heteroassociative networks. In the paper, the global asymptotic stability is studied for continuous bi-directional associative memory neural networks with axonal signal transmission delay while the neuronal output signal function S is not differentiable and strictly monotone increasing. Several sufficient conditions guaranteeing the network´s global asymptotic stability are derived, the obtained results have important leading significance in the design and application of BAM
Keywords :
asymptotic stability; content-addressable storage; delays; multilayer perceptrons; stability criteria; BAM; axonal signal transmission delay; bi-directional associative memory neural networks; delay; global asymptotic stability; nondifferentiable output signal function; stability conditions; strictly monotone increasing output signal function; two-layer heteroassociative networks; Artificial neural networks; Associative memory; Asymptotic stability; Bidirectional control; Correlators; Delay effects; Educational institutions; Magnesium compounds; Neural networks; Sufficient conditions;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863341
