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Interpolation and Approximation of Models

  • Bruno Pelletier
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)

Abstract

A global approach may not be well suited for the approximation of complex and high-dimensional input-output mappings, inadequacy being defined in terms of complexity and/or accuracy. In this paper, a global modelling method from a set of locally optimal simpler models is presented. Theoretical aspects of interpolation and approximation of models are addressed. The method has been applied to the remote sensing of ocean color from space where it has shown good results in comparison with global approaches based on multilayer perceptrons and radial basis functions networks.

Keywords

Radial Basis Function Neural Network Radial Basis Function Network Global Approach Ocean Color Phytoplankton Concentration 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Bruno Pelletier
    • 1
  1. 1.ONERA-CERT, DTIMToulouse CedexFrance

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