Combination of vector quantization and visualization

Abstract

In this paper, we present a comparative analysis of a combination of two vector quantization methods (self-organizing map and neural gas), based on a neural network and multidimensional scaling that is used for visualization of codebook vectors obtained by vector quantization methods. The dependence of computing time on the number of neurons, the ratio between the number of neuron-winners and that of all neurons, quantization and mapping qualities, and preserving of a data structure in the mapping image are investigated. © 2009 Springer Berlin Heidelberg.