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Preprocessing In Attractor Neural Networks

Author

Listed:
  • C.G. CARVALHAES

    (Instituto de Física, Universidade Federal Fluminense Av. Litorâmpa, s/m, Boa Viagem, Niterói, RJ, Brazil)

  • A.T. COSTA

    (Instituto de Física, Universidade Federal Fluminense Av. Litorâmpa, s/m, Boa Viagem, Niterói, RJ, Brazil)

  • T.J.P. PENNA

    (Instituto de Física, Universidade Federal Fluminense Av. Litorâmpa, s/m, Boa Viagem, Niterói, RJ, Brazil)

Abstract

Preprocessing the input patterns seems the simplest approach to invariant pattern recognition by neural networks. The Fourier transform has been proposed as an appropriate and elegant preprocessor. Nevertheless, we show in this work that the performance of this kind of preprocessor is strongly affected by the number of stored informations. This is so because the phase of the Fourier transform plays a more important role than the amplitude in the recognition process.

Suggested Citation

  • C.G. Carvalhaes & A.T. Costa & T.J.P. Penna, 1995. "Preprocessing In Attractor Neural Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-10.
    • Handle: RePEc:wsi:ijmpcx:v:06:y:1995:i:01:n:s0129183195000022
    DOI: 10.1142/S0129183195000022
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