Abstract
FastICA is arguably one of the most widespread methods for independent component analysis. We focus on its deflation-based implementation, where the independent components are extracted one after another. The present contribution evaluates the method's speed in terms of the overall computational complexity required to reach a given source extraction performance. FastICA is compared with a simple modification referred to as RobustICA, which merely consists of performing exact line search optimization of the kurtosis-based contrast function. Numerical results illustrate the speed limitations of FastICA. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Zarzoso, V., & Comon, P. (2007). Comparative speed analysis of FastICA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 293–300). Springer Verlag. https://doi.org/10.1007/978-3-540-74494-8_37
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