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Post Nonlinear Independent Subspace Analysis

Szabo, Z; Póczos, B; Szirtes, G; Lőrincz, A; (2007) Post Nonlinear Independent Subspace Analysis. In: Sa, JM and Alexandre, LA and Duch, W and Mandic, DP, (eds.) Artificial Neural Networks – ICANN 2007: Proceedings of the 17th International Conference, Porto, Portugal, September 9-13, 2007, Part I. (pp. 677 - 686). Springer-Verlag, Berlin Heidelberg Green open access

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Abstract

In this paper a generalization of Post Nonlinear Independent Component Analysis (PNL-ICA) to Post Nonlinear Independent Subspace Analysis (PNL-ISA) is presented. In this framework sources to be identified can be multidimensional as well. For this generalization we prove a separability theorem: the ambiguities of this problem are essentially the same as for the linear Independent Subspace Analysis (ISA). By applying this result we derive an algorithm using the mirror structure of the mixing system. Numerical simulations are presented to illustrate the efficiency of the algorithm.

Type: Proceedings paper
Title: Post Nonlinear Independent Subspace Analysis
Event: International Conference on Artificial Neural Networks (ICANN 2007)
Location: Porto, Portugal
Dates: 2007-09-09 - 2007-09-13
ISBN-13: 978-3-540-74689-8
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-540-74690-4_69
Publisher version: http://dx.doi.org/10.1007/978-3-540-74690-4_69
Language: English
Additional information: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-74690-4_69
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/1433230
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