Abstract
In high dimensional data analysis, finding non-Gaussian components is an important preprocessing step for efficient information processing. By modifying the contrast function of JADE algorithm for Independent Component Analysis, we propose a new linear dimension reduction method to identify the non-Gaussian subspace based on the fourth-order cumulant tensor. A numerical study demonstrates the validity of our method and its usefulness for extracting sub-Gaussian structures. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Kawanabe, M. (2005). Linear dimension reduction based on the fourth-order cumulant tensor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 151–156). https://doi.org/10.1007/11550907_25
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