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Assesing the Noise Immunity of Radial Basis Function Neural Networks

  • J. L. Bernier
  • J. González
  • A. Cañas
  • J. Ortega
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2085)

Abstract

Previous works have demonstrated that Mean Squared Sensitivity (MSS) constitutes a good aproximation to the performance degradation of a MLP affected by perturbations. In the present paper, the expression of MSS for Radial Basis Function Neural Networks affected by additive noise in their inputs is obtained. This expression is experimentally validated, allowing us to propose MSS as an effective measurement of noise immunity of RBFNs.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • J. L. Bernier
    • 1
  • J. González
    • 1
  • A. Cañas
    • 1
  • J. Ortega
    • 1
  1. 1.Dpto. Arquitectura y Tecnologia de ComputadoresUniversidad de Granada

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