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ESANN
2004

Linearization identification and an application to BSS using a SOM

9 years 8 months ago
Linearization identification and an application to BSS using a SOM
The one-dimensional functional equation g(y(t)) = cg(z(t)) with known functions y and z and constant c is considered. The indeterminacies are calculated, and an algorithm for approximating g given y and z at finitely many time instants is proposed. This linearization identification algorithm is applied to the postnonlinear blind source separation (BSS) problem in the case of independent sources with bounded densities. A self-organizing map (SOM) is used to approximate the boundary, and the postnonlinearity estimation in this multivariate case is reduced to the one-dimensional functional equation from above.
Fabian J. Theis, Elmar Wolfgang Lang
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Where ESANN
Authors Fabian J. Theis, Elmar Wolfgang Lang
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