A hybrid projection based and radial basis function architecture

  • Shimon Cohen
  • Nathan Intrator
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1857)

Abstract

A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Shimon Cohen
    • 1
  • Nathan Intrator
    • 1
  1. 1.Computer Science DepartmentTel-Aviv UniversityIsrael

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