A review of independent component analysis (ICA) based on Kurtosis Contrast Function
Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis co...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
INSInet Publications
2011
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/44703/ |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis contrast function. We briefly present the common independent component analysis algorithms that use Kurtosis as a criterion for non-Gaussian. Basid on the literatures, we compare these algrithms in terms of performance and advantaves. |
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