Fast Kernel-Based Independent Component Analysis
Recent approaches to independent component analysis (ICA) have used kernel independence measures to obtain highly accurate solutions, particularly where classical methods experience difficulty (for instance, sources with near-zero kurtosis). FastKICA (fast HSIC-based kernel ICA) is a new optimization method for one such kernel independence measure, the Hilbert-Schmidt Independence Criterion (HSIC). The high computational efficiency of this approach is achieved by combining geometric...[Show more]
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|Source:||IEEE Transactions on Signal Processing|
|01_Shen_Fast_Kernel-Based_Independent_2009.pdf||701.14 kB||Adobe PDF||Request a copy|
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