Functional Radial Basis Function Network (FRBFN)

Delannay, Nicolas;Rossi, Fabrice;Conan-Guez, B.;Verleysen, Michel
(2004) ESANN 2004, European Symposium on Artificial Neural Networks — Location: Bruges (Belgium) (28.April.2004)

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Authors
  • Delannay, NicolasUCLouvain
    Author
  • Rossi, FabriceUniversité Paris-Dauphine
    Author
  • Conan-Guez, B.Université Paris-Dauphine
    Author
  • Verleysen, MichelUCLouvain
    Author
Abstract
There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric models [3], MLP [4]). The main motivation of these methods is to benefit from the enforced inner structure of the data. This paper presents how functional data can be used with RBFN, and how the inner structure of the former can help designing the network.
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Delannay, N., Rossi, F., Conan-Guez, B., & Verleysen, M. (2004). Functional Radial Basis Function Network (FRBFN). Proceedings of ESANN 2004, European Symposium on Artificial Neural Networks, p. 313-318. https://hdl.handle.net/2078.5/220965