Title :
Vector quantization for multiple classes
Author :
Abou-Ali, Awel-Latief H. ; Porter, William A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Alabama Univ., Huntsville, AL, USA
Abstract :
Vector quantization algorithms have long been used to find a finite set of exemplars which represent a data set to within an a priori error tolerance. Such a representation is essential in codebook-based data compression and transmission. The present study considers the situation where the data to be encoded consists of subclasses. The codebook must provide information compression within the several subclasses; however, minimization of interclass errors is of equal importance. We present modifications to a basic vector quantization (VQ) algorithm which adapts it to the multiclass vector quantizing setting. We then explore the behavior of the modified algorithm on selected benchmark applications. We show, in particular, that overlapping subclasses can be accommodated by the algorithm
Keywords :
data structures; pattern classification; signal processing; vector quantisation; benchmark applications; codebook; codebook-based data compression; data set; information compression; minimization of interclass errors; modified algorithm; multiclass vector quantisation; multiple classes; overlapping subclasses; representation; subclasses.; Clustering algorithms; Computer errors; Data compression; Decoding; Helium; Iterative algorithms; Kernel; Nearest neighbor searches; Training data; Vector quantization;
Conference_Titel :
Aerospace Conference, 1997. Proceedings., IEEE
Conference_Location :
Snowmass at Aspen, CO
Print_ISBN :
0-7803-3741-7
DOI :
10.1109/AERO.1997.577500
