A neural network for the blind separation of non-Gaussian sources
Bernd Freisleben, Claudia Hagen, Markus Borschbach · 2002
In this paper, a two-layer neural network is presented, which organizes itself to perform blind source separation. The inputs to the network are prewhitened linear mixtures of unknown independent source signals. An unsupervised nonlinear Hebbian learning rule is used for training the network. After convergence, the network is able to extract the source signals from the mixtures, provided that the source signals do not have Gaussian distributions.