A Synergetic Neural Network with Crosscorrelation Dynamics

Masahiro NAKAGAWA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A   No.5   pp.881-893
Publication Date: 1997/05/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Neural Networks
bidirectional association,  synergetic neurons,  dynamics of associative memory,  

Full Text: PDF(720.9KB)>>
Buy this Article

In this study we shall put forward a bidirectional synergetic neural network and investigate the crossassociation dynamics in an order parameter space. The present model is substantially based on a top-down formulation of the dynamic rule of an analog neural network in the analogy with the conventional bidirectional associative memory. It is proved that a complete association can be assured up to the same number of the embedded patterns as the number of neurons. In addition, a searching process of a couple of embedded patterns can be also realised by means of controlling attraction parameters as seen in the autoassociative synergetic models.