Fast search algorithms for vector quantization and pattern matching

Abstract

A fundamental computational task that arises in several areas of signal processing is pattern matching, where a given test pattern is compared with a large set of stored templates, to find the best match that minimizes a given measure of dissimilarity. Three different geometrically-oriented methods are proposed for substantially reducing the computational complexity of the search process by reducing the number of multiplies in exchange for additional low complexity operations and, in two of the methods, additional memory for storing precomputed tables.