Independent Component Analysis of Fixed-Point Algorithm for Clustering Components Using Kurtosis


The KIPS Transactions:PartB , Vol. 11, No. 3, pp. 381-386, Jun. 2004
10.3745/KIPSTB.2004.11.3.381,   PDF Download:

Abstract

This paper proposes an independent component analysis(ICA) of the fixed-point(FP) algorithm based on Newton method by adding the kurtosis. The kurtosis is applied for clustering the components, and the FP algorithm of Newton method is applied for improving the analysis speed and performance. The proposed ICA has been applied to the problems for separating the 6-mixed signals of 500 samples and 8-mixed images of 512X512 pixels, respectively. The experimental results show that the proposed ICA has always a fixed analysis sequence. The result can be solved the limit of conventional ICA which has a variable sequence depending on the running of algorithm. Especially, the proposed ICA can be used to classify and identify the signals or the images.


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Cite this article
[IEEE Style]
Y. H. Cho and A. R. Kim, "Independent Component Analysis of Fixed-Point Algorithm for Clustering Components Using Kurtosis," The KIPS Transactions:PartB , vol. 11, no. 3, pp. 381-386, 2004. DOI: 10.3745/KIPSTB.2004.11.3.381.

[ACM Style]
Yong Hyun Cho and A Ram Kim. 2004. Independent Component Analysis of Fixed-Point Algorithm for Clustering Components Using Kurtosis. The KIPS Transactions:PartB , 11, 3, (2004), 381-386. DOI: 10.3745/KIPSTB.2004.11.3.381.