A Modified Fuzzy ARTMAP Architecture for Incremental Learning Function Approximation

摘要

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 approximation. FAMR uses a relevance factor assigned to each sample pair, proportional to the importance of the respective pair during the learning phase, and is a generalization of PROBART (a FAM architecture defined in [2]). Like other FAM-based systems, FAMR can be incrementally trained.