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Radial Basis Function Networks

  • Rudolf Kruse
  • Christian Borgelt
  • Frank Klawonn
  • Christian Moewes
  • Matthias Steinbrecher
  • Pascal Held
Part of the Texts in Computer Science book series (TCS)

Abstract

Like multi-layer perceptrons, radial basis function networks are feed-forward neural networks with a strictly layered structure. However, the number of layers is always three, that is, there is exactly one hidden layer. In addition, radial basis function networks differ from multi-layer perceptrons in the network input and activation functions, especially in the hidden layer. In this hidden layer radial basis functions are employed, which are responsible for the name of this type of neural network. With these functions a kind of “catchment region” is assigned to each neuron, in which it mainly influences the output of the neural network.

Keywords

Hide Layer Radial Basis Function Activation Function Weight Vector Input Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. A. Albert. Regression and the Moore-Penrose Pseudoinverse. Academic Press, New York, NY, USA, 1972 zbMATHGoogle Scholar
  2. J.A. Hartigan and M.A. Wong. A k-means Clustering Algorithm. Applied Statistics 28:100–108. Blackwell, Oxford, United Kingdom, 1979 zbMATHCrossRefGoogle Scholar
  3. A. Zell. Simulation Neuronaler Netze. Addison-Wesley, Stuttgart, Germany, 1996 Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Rudolf Kruse
    • 1
  • Christian Borgelt
    • 2
  • Frank Klawonn
    • 3
  • Christian Moewes
    • 1
  • Matthias Steinbrecher
    • 4
  • Pascal Held
    • 1
  1. 1.Faculty of Computer ScienceOtto-von-Guericke University MagdeburgMagdeburgGermany
  2. 2.Intelligent Data Analysis & Graphical Models Research UnitEuropean Centre for Soft ComputingMieresSpain
  3. 3.FB InformatikOstfalia University of Applied SciencesWolfenbüttelGermany
  4. 4.SAP Innovation CenterPotsdamGermany

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