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Radial Basis Function Networks

Chapter

Abstract

Learning is an approximation problem, which is closely related to the conventional approximation techniques, such as generalized splines and regularization techniques. The RBF network has its origin in performing exact interpolation of a set of data points in a multidimensional space [81]. The RBF network is a universal approximator, and it is a popular alternative to the MLP, since it has a simpler structure and a much faster training process. Both models are widely used for classification and function approximation.

Keywords

Extreme Learning Machine Hide Node Hide Unit Probabilistic Neural Network Wavelet Neural Network 
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 London 2014

Authors and Affiliations

  1. 1.Enjoyor LabsEnjoyor Inc.HangzhouChina
  2. 2.Department of Electrical and Computer EngineeringConcordia UniversityMontrealCanada

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