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# Nonlinear Independent Component Analysis Using Ensemble Learning:
Theory

**Harri Valpola**

Helsinki University of Technology, Neural Networks Research Centre

P.O.Box 5400, FIN-02015 HUT, Espoo, Finland

E-mail: `Harri.Valpola@hut.fi` URL: `http://www.cis.hut.fi/`

### Abstract:

A nonlinear version of independent component analysis is presented.
The mapping from sources to observations is modelled by a
multi-layer perceptron network and the distributions of sources are
modelled by mixtures of Gaussians. The posterior probability of all
the unknown parameters is estimated by ensemble learning. In this
paper, we present the theory of the method, and in a companion paper
experimental results.

*Harri Valpola*

*2000-03-03*