A competitive learning algorithm for separating binary sources

摘要

A neural algorithm for separating binary sources from their linear unknown mixtures is presented. The a priori knowledge of binary sources is utilized by using competitive learning. With the algorithm it is possible to handle the difficult case of separating more sources than sensors. When the mixtures are noisy, it is possible to recover the sources exactly when the noise level is low.