Paper No: 102
Speed and Accuracy Enhancement of Linear ICA Techniques Using Rational Nonlinear Functions
Author(s): Petr Tichavsky, Zbynek Koldovsky, Erkki Oja
Abstract
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. |
