Jornal article

Tichavský P., Koldovský Z., Oja E.

Lecture Notes in Computer Science

2007

4666 (2007)

285-292

0302-9743

Ing. Petr Tichavský, CSc. (ÚTIA - Oddělení stochastické informatiky)

blind source separation, independent component analysis

Many linear ICA techniques are based on minimizing a nonlinear contrast function and many of them use a hyperbolic tangent (tanh) as their built-in nonlinearity. In this paper we propose two rational functions to replace the tanh and other popular functions that are tailored for separating supergaussian (long-tailed) sources. The advantage of the rational function is two-fold. First, the rational function requires a significantly lower computational complexity than tanh, e.g. nine times lower. As a result, algorithms using the rational functions are typically twice faster than algorithms with tanh. Second, it can be shown that a suitable selection of the rational function allows to achieve a better performance of the separation in certain scenarios. This improvement might be systematic, if the rational nonlinearities are selected adaptively to data.