**Harri Valpola and Petteri Pajunen**

Helsinki University of Technology, Neural Networks Research Centre

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

E-mail: `Harri.Valpola@hut.fi`, `Petteri.Pajunen@hut.fi`

URL: `http://www.cis.hut.fi/`

Fast algorithms for linear blind source separation are developed.
The fast convergence is first derived from low-noise approximation of
the EM-algorithm given in [2], to which a modification is made
that leads as a special case to the FastICA algorithm [5].
The modification is given a general interpretation and is applied to
Bayesian blind source separation of noisy signals.

- Introduction
- EM-algorithm for Independent Component Analysis
- Fast EM-algorithm by Filtering of Gaussian Noise
- FastICA as EM-Algorithm with Filtering of Gaussian Noise
- Application to General ICA Algorithms
- Application to Bayesian Noisy ICA
- Experiments
- Discussion
- Bibliography
- About this document ...