Szabo, Z;
Póczos, B;
Lőrincz, A;
(2005)
Separation Theorem for Independent Subspace Analysis.
: Eötvös Loránd University, Budapest.
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Abstract
Here, a separation theorem about Independent Subspace Analysis (ISA), a generalization of Independent Component Analysis (ICA) is proven. According to the theorem, ISA estimation can be executed in two steps under certain conditions. In the first step, 1-dimensional ICA estimation is executed. In the second step, optimal permutation of the ICA elements is searched for. We shall show that elliptically symmetric sources, among others, satisfy the conditions of the theorem.
| Type: | Report |
|---|---|
| Title: | Separation Theorem for Independent Subspace Analysis |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| UCL classification: | UCL > Provost and Vice Provost Offices 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 UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1433236 |
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