Szabo, Z;
Lőrincz, A;
(2009)
Complex Independent Process Analysis.
Acta Cybernetica
, 19
177 - 190.
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Abstract
We present a general framework for the search of hidden independent processes in the complex domain. The task is to estimate the hidden independent multidimensional complex-valued components observing only the mixture of the processes driven by them. In our model (i) the hidden independent processes can be multidimensional, they may be subject to (ii) moving averaging, or may evolve in an autoregressive manner, or (iii) they can be non-stationary. These assumptions are covered by integrated autoregressive moving average processes and thus our task is to solve their complex extensions. We show how to reduce the undercomplete version of complex integrated autoregressive moving average processes to real independent subspace analysis that we can solve. Simulations illustrate the working of the algorithm.
| Type: | Article |
|---|---|
| Title: | Complex Independent Process Analysis |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.inf.u-szeged.hu/actacybernetica/edb/vol... |
| 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/1433161 |
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