A Modified Fuzzy ARTMAP Architecture for Incremental Learning Function Approximation

R. Andonie, L. Sasu (Romania), and V. Beiu (USA)

Keywords

Fuzzy ARTMAP, function approximation, incrementallearning

Abstract

We will focus here on approximating functions that map from the vector-valued real domain to the vector-valued real range. A Fuzzy ARTMAP (FAM) architecture, called Fuzzy Artmap with Relevance factor (FAMR, defined in [1]) is considered here as an alternative to function approx imation. FAMR uses a relevance factor assigned to each sample pair, proportional to the importance of the respec tive pair during the learning phase, and is a generalization of PROBART (a FAM architecture defined in [2]). Like other FAMbased systems, FAMR can be incrementally trained.

Important Links:

• DOI:
• From Proceeding (389) Neural Networks and Computational Intelligence - 2003

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