Póczos, B;
Szabo, Z;
Kiszlinger, M;
Lőrincz, A;
(2007)
Independent Process Analysis without A Priori Dimensional Information.
In: Davies, ME and James, CJ and Abdallah, SA and Plumbley, MD, (eds.)
Independent Component Analysis and Signal Separation: Proceedings of the 7th International Conference, ICA 2007, London, UK, September 9-12, 2007.
(pp. 252 - 259).
Springer-Verlag Heidelberg
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Abstract
Recently, several algorithms have been proposed for independent subspace analysis where hidden variables are i.i.d. processes. We show that these methods can be extended to certain AR, MA, ARMA and ARIMA tasks. Central to our paper is that we introduce a cascade of algorithms, which aims to solve these tasks without previous knowledge about the number and the dimensions of the hidden processes. Our claim is supported by numerical simulations. As an illustrative application where the dimensions of the hidden variables are unknown, we search for subspaces of facial components.
Type: | Proceedings paper |
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Title: | Independent Process Analysis without A Priori Dimensional Information |
Event: | International Conference on Independent Component Analysis and Signal Separation (ICA) |
Location: | London, UK |
Dates: | 2007-09-09 - 2007-09-12 |
ISBN-13: | 978-3-540-74493-1 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-540-74494-8_32 |
Publisher version: | http://dx.doi.org/10.1007/978-3-540-74494-8_32 |
Language: | English |
Additional information: | This is the authors' accepted version of this published article. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-74494-8_32 |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences |
URI: | https://discovery.ucl.ac.uk/id/eprint/1433231 |




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