Statistical Pattern Recognition Problems and the Multiple Classes Random Neural Network Model

  • Jose Aguilar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)

Abstract

The purpose of this paper is to describe the use of the multiple classes random neural network model to learn various statistical patterns. We propose a pattern recognition algorithm for the recognition of statistical patterns based upon the non-linear equations of the multiple classes random neural network model using gradient descent of a quadratic error function. In this case the classification errors are considered.

Keywords

Statistical Pattern Zernike Moment Pattern Recognition Problem Pattern Recognition Algorithm Statistical Pattern Recognition 
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 2004

Authors and Affiliations

  • Jose Aguilar
    • 1
  1. 1.CEMISID, Dpto. de Computación, Facultad de IngenieríaUniversidad de los AndesMéridaVenezuela

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