Title

A Dynamical Adaptive Resonance Architecture

Abstract

A set of nonlinear differential equations that describe the dynamics of the ART1 model are presented, along with the motivation for their use. These equations are extensions of those developed by Carpenter and Grossberg [1], It is shown how these differential equations allow the ART1 model to be realized as a collective nonlinear dynamical system. Specifically, we present an ART 1-based neural network model whose description requires no external control features. That is, the dynamics of the model are completely determined by the set of coupled differential equations that comprise the model. It is shown analytically how the parameters of this model can be selected so as to guarantee a behavior equivalent to that of ART1 in both fast and slow learning scenarios. Simulations are performed in which the trajectories of node and weight activities are determined using numerical approximation techniques. © 1994 IEEE

Publication Date

1-1-1994

Publication Title

IEEE Transactions on Neural Networks

Volume

5

Issue

6

Number of Pages

873-889

Document Type

Article

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/72.329684

Socpus ID

0028546055 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0028546055

This document is currently not available here.

Share

COinS