Title :
Quantization, classification, and density estimation for Kohonen´s Gaussian mixture
Author :
Gray, Robert M. ; Perlmutter, Keren O. ; Olshen, Richard A.
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
fDate :
30 Mar-1 Apr 1998
Abstract :
We consider the problem of joint quantization and classification for the example of a simple Gaussian mixture used by Kohonen (1988) to demonstrate the performance of his “learning vector quantization” (LVQ). Implicit in the problem is the issue of estimating the underlying densities, which is accomplished by CARTTM and by an inverse halftoning method
Keywords :
Bayes methods; Gaussian processes; image classification; image coding; inverse problems; learning (artificial intelligence); parameter estimation; self-organising feature maps; vector quantisation; Bayes VQ; CART; Kohonen´s Gaussian mixture; LVQ; classification; image coding; inverse halftoning method; learning vector quantization; optimality properties; probability density estimation; Bit rate; Cost function; Decoding; Distortion measurement; Information systems; Laboratories; Lagrangian functions; Random processes; Rate distortion theory; Vector quantization;
Conference_Titel :
Data Compression Conference, 1998. DCC '98. Proceedings
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-8406-2
DOI :
10.1109/DCC.1998.672132
