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http://dx.doi.org/10.3745/KIPSTB.2004.11B.2.199

Hybrid ICA of Fixed-Point Algorithm and Robust Algorithm Using Adaptive Adaptation of Temporal Correlation  

Cho, Yong-Hyun (대구가톨릭대학교 컴퓨터정보통신공학부)
Oh, Jeung-Eun (㈜아바드 연구원)
Publication Information
The KIPS Transactions:PartB / v.11B, no.2, 2004 , pp. 199-206 More about this Journal
Abstract
This paper proposes a hybrid independent component analysis(ICA) of fixed-point(FP) algorithm and robust algorithm. The FP algorithm is applied for improving the analysis speed and performance, and the robust algorithm is applied for preventing performance degradations by means of very small kurtosis and temporal correlations between components. And the adaptive adaptation of temporal correlations has been proposed for solving limits of the conventional robust algorithm dependent on the maximum time delay. The proposed ICA has been applied to the problems for separating the 4-mixed signals of 500 samples and 10-mixed images of $512\times512$pixels, respectively. The experimental results show that the proposed ICA has a characteristics of adaptively adapting the maximum time delay, and has a superior separation performances(speed, rate) to conventional FP-ICA and hybrid ICA of heuristic correlation. Especially, the proposed ICA gives the larger degree of improvement as the problem size increases.
Keywords
Independent Component Analysis; Fixed-Point Algorithm; Robust Algorithm; Kurtosis; Blind Source Separation;
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