An adaptive geometrical procedure for blind separation of sources

摘要

In many Signal Processing applications, data sampled by sensors comprise a mixture of signals from different sources. The problem of blind separation lies in the reconstruction of sources from the mixtures. In this paper a new method is proposed for the separation of sources, based on geometrical considerations. After a brief introduction, we present the principles of the new method and provide a description of the algorithm and map this on an artificial neural network. Finally we give examples with synthetic and real signals to illustrate the efficiency and utility of the network.