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|Title:||Data clustering using higher order statistics|
|Citation:||IEEE TENCON'97 - IEEE REGIONAL 10 ANNUAL CONFERENCE, PROCEEDINGS, VOLS 1 AND 2: SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS,803-806|
|Abstract:||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.|
|Appears in Collections:||Proceedings papers|
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