Genetic Fuzzy Relational Neural Network for Infant Cry Classification

  • Alejandro Rosales-Pérez
  • Carlos A. Reyes-García
  • Pilar Gómez-Gil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6718)

Abstract

In this paper we describe a genetic fuzzy relational neural network (FRNN) designed for classification tasks. The genetic part of the proposed system determines the best configuration for the fuzzy relational neural network. Besides optimizing the parameters for the FRNN, the fuzzy membership functions are adjusted to fit the problem. The system is tested in several infant cry database reaching results up to 97.55%. The design and implementation process as well as some experiments along with their results are shown.

Keywords

Fuzzy relational neural network genetic algorithm infant cry classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alejandro Rosales-Pérez
    • 1
  • Carlos A. Reyes-García
    • 1
  • Pilar Gómez-Gil
    • 1
  1. 1.Computer Science DepartmentNational Institute of Astrophysics, Optics and Electronics (INAOE)PueblaMéxico

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