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An adaptive geometrical procedure for blind separation of sources

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Abstract

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.

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Authors and Affiliations

  1. Departamento de Electronica y Tecnologia de Computadores Facultad de Ciencias, Universidad de Granada Campus Universitario de Fuentenueva, E-18071, Granada, Spain

    Carlos G. Puntonet & Alberto Prieto

Authors
  1. Carlos G. Puntonet
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  2. Alberto Prieto
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Puntonet, C.G., Prieto, A. An adaptive geometrical procedure for blind separation of sources. Neural Process Lett 2, 23–27 (1995). https://doi.org/10.1007/BF02332162

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