Record Details

Data clustering using higher order statistics

DSpace at IIT Bombay

View Archive Info
 
 
Field Value
 
Title Data clustering using higher order statistics
 
Creator RAJAGOPALAN, AN
YEASIN, M
CHAUDHURI, S
 
Description Traditional k-means algorithms for data clustering are based on the assumption that the underlying distribution of the data is Gaussian. In this paper, we propose a new clustering algorithm that makes use of higher order statistics for improved data clustering when the distribution of the data is non-Gaussian. The algorithm uses an HOS-based decision measure which is derived from a series expansion of the multivariate probability density function in terms of the multivariate Gaussian and the Hermite polynomials. Experimental results are presented on the performance of the proposed algorithm.
 
Publisher IEEE
 
Date 2011-10-25T12:05:43Z
2011-12-15T09:11:53Z
2011-10-25T12:05:43Z
2011-12-15T09:11:53Z
1997
 
Type Proceedings Paper
 
Identifier IEEE TENCON'97 - IEEE REGIONAL 10 ANNUAL CONFERENCE, PROCEEDINGS, VOLS 1 AND 2: SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS,803-806
0-7803-4365-4
0886-1420
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15715
http://hdl.handle.net/100/2356
 
Source IEEE Region 10 Annual Conference on Speech and Image Technologies for Computing and Telecommunications (IEEE TENCON 97),BRISBANE, AUSTRALIA,DEC 02-04, 1997
 
Language English