Fuzzy concepts in vector quantization training

Authors:
Francesco Masulli;Stefano Rovetta
Affiliations:
Department of Computer Science, University of Pisa, Italy;Department of Computer and Information Sciences, University of Genoa, Italy
Venue:
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
Year:
2003

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Abstract

Vector quantization and clustering are two different problems for which similar techniques are used. We analyze some approaches to the synthesis of a vector quantization codebook, and their similarities with corresponding clustering algorithms. We outline the role of fuzzy concepts in the performance of these algorithms, and propose an alternative way to use fuzzy concepts as a modeling tool for physical vector quantization systems, Neural Gas with a fuzzy rank function.