Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
411004 | Neurocomputing | 2006 | 17 Pages |
Abstract
This paper presents a new approach to incrementally constructing a neural network that is capable of learning new information without forgetting old knowledge. The proposed neural network, called hyper-spherical ARTMAP network (HS-ARTMAP network), is a synthesis of an RBF-network-like module and an ART-like module. The HS-ARTMAP network is trained via a training algorithm similar to the training algorithm for the fuzzy ARTMAP system. To demonstrate the performance of the proposed HS-ARTMAP network, several pattern recognition and function approximation problems were tested.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Mu-Chun Su, Jonathan Lee, Kuo-Lung Hsieh,