D-ART: a pattern recognition system based on adaptive resonance and algebraic metric space theories

Summary form only given, as follows. The authors discuss combining the adaptive resonance theory of neural networks with results from algebraic metric space theory. The notion of the so-called dual planes is adapted to Carpenter and Grossberg's adaptive resonance theory systems (hence the name...

Full description

Saved in:
Bibliographic Details
Main Authors: Zikan, K., Caudell, T.P.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive systems
Capacity planning
Extraterrestrial measurements
Information geometry
Neural networks
Pattern analysis
Pattern recognition
Resonance
Subspace constraints
Systems engineering and theory
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Summary form only given, as follows. The authors discuss combining the adaptive resonance theory of neural networks with results from algebraic metric space theory. The notion of the so-called dual planes is adapted to Carpenter and Grossberg's adaptive resonance theory systems (hence the name D-ART). The new system is appropriate for a large class of applications, for instance, 'sparse' images, e.g., wire-frame or constellation data. Unlike the classical ART, D-ART explicitly utilizes the geometry of the underlying space.< >
DOI:10.1109/IJCNN.1991.155600