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Fast tensorial JADE

We propose a novel method for tensorial‐independent component analysis. Our approach is based on TJADE and k‐JADE, two recently proposed generalizations of the classical JADE algorithm. Our novel method achieves the consistency and the limiting distribution of TJADE under mild assumptions and at the...

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Autores principales: Virta, Joni, Lietzén, Niko, Ilmonen, Pauliina, Nordhausen, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891388/
https://www.ncbi.nlm.nih.gov/pubmed/33664538
http://dx.doi.org/10.1111/sjos.12445
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author Virta, Joni
Lietzén, Niko
Ilmonen, Pauliina
Nordhausen, Klaus
author_facet Virta, Joni
Lietzén, Niko
Ilmonen, Pauliina
Nordhausen, Klaus
author_sort Virta, Joni
collection PubMed
description We propose a novel method for tensorial‐independent component analysis. Our approach is based on TJADE and k‐JADE, two recently proposed generalizations of the classical JADE algorithm. Our novel method achieves the consistency and the limiting distribution of TJADE under mild assumptions and at the same time offers notable improvement in computational speed. Detailed mathematical proofs of the statistical properties of our method are given and, as a special case, a conjecture on the properties of k‐JADE is resolved. Simulations and timing comparisons demonstrate remarkable gain in speed. Moreover, the desired efficiency is obtained approximately for finite samples. The method is applied successfully to large‐scale video data, for which neither TJADE nor k‐JADE is feasible. Finally, an experimental procedure is proposed to select the values of a set of tuning parameters. Supplementary material including the R‐code for running the examples and the proofs of the theoretical results is available online.
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spelling pubmed-78913882021-03-02 Fast tensorial JADE Virta, Joni Lietzén, Niko Ilmonen, Pauliina Nordhausen, Klaus Scand Stat Theory Appl Original Articles We propose a novel method for tensorial‐independent component analysis. Our approach is based on TJADE and k‐JADE, two recently proposed generalizations of the classical JADE algorithm. Our novel method achieves the consistency and the limiting distribution of TJADE under mild assumptions and at the same time offers notable improvement in computational speed. Detailed mathematical proofs of the statistical properties of our method are given and, as a special case, a conjecture on the properties of k‐JADE is resolved. Simulations and timing comparisons demonstrate remarkable gain in speed. Moreover, the desired efficiency is obtained approximately for finite samples. The method is applied successfully to large‐scale video data, for which neither TJADE nor k‐JADE is feasible. Finally, an experimental procedure is proposed to select the values of a set of tuning parameters. Supplementary material including the R‐code for running the examples and the proofs of the theoretical results is available online. John Wiley and Sons Inc. 2020-02-11 2021-03 /pmc/articles/PMC7891388/ /pubmed/33664538 http://dx.doi.org/10.1111/sjos.12445 Text en © 2020 The Authors. Scandinavian Journal of Statistics published by John Wiley & Sons Ltd on behalf of The Board of the Foundation of the Scandinavian Journal of Statistics. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Virta, Joni
Lietzén, Niko
Ilmonen, Pauliina
Nordhausen, Klaus
Fast tensorial JADE
title Fast tensorial JADE
title_full Fast tensorial JADE
title_fullStr Fast tensorial JADE
title_full_unstemmed Fast tensorial JADE
title_short Fast tensorial JADE
title_sort fast tensorial jade
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891388/
https://www.ncbi.nlm.nih.gov/pubmed/33664538
http://dx.doi.org/10.1111/sjos.12445
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