Efficient Variant of Algorithm FastICA for Independent Component Analysis Attaining the CramÉr-Rao Lower Bound

FastICA is one of the most popular algorithms for independent component analysis (ICA), demixing a set of statistically independent sources that have been mixed linearly. A key question is how accurate the method is for finite data samples. We propose an improved version of the FastICA algorithm whi...

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Veröffentlicht in:	IEEE transactions on neural networks Jg. 17; H. 5; S. 1265 - 1277
Hauptverfasser:	Koldovsky, Z., Tichavsky, P., Oja, E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.09.2006 Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithm FastICA Algorithms Applied sciences Artificial Intelligence Asymptotic properties Automation blind deconvolution blind source separation Computational complexity Computational modeling Computer science; control theory; systems Computer Simulation Computing Methodologies Connectionism. Neural networks CramÉr-Rao lower bound (CRB) Data Interpretation, Statistical Deconvolution Errors Exact sciences and technology Independent component analysis independent component analysis (ICA) Information theory Lower bounds Matlab Models, Statistical Neural networks Pattern Recognition, Automated - methods Principal Component Analysis Probability distribution Signal processing Signal processing algorithms Signal Processing, Computer-Assisted Speech Source separation Cramér-Rao lower bound (CRB) independent component analysis (ICA) Independent component analysis Error bound Blind deconvolution Neural network Computational complexity Algorithm FastICA blind source separation Algorithm analysis Blind separation
ISSN:	1045-9227, 1941-0093
Online-Zugang:	Volltext
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