An Introduction to Information Theoretic Learning, Part II: Applications

  • Daniel Silva University of Brasília
  • Denis Fantinato University of Campinas
  • Janio Canuto Federal University of Sergipe
  • Leonardo Duarte University of Campinas
  • Aline Neves Federal University of ABC
  • Ricardo Suyama Federal University of ABC
  • Jugurta Montalvão Federal University of Sergipe
  • Romis Attux University of Campinas
Keywords: ITL, information theory, entropy, correntropy

Abstract

This is the second part of the introductory tutorial about information theoretic learning, which, after the theoretical foundations presented in Part I, now discusses the concepts of correntropy, a new similarity measure derived from the quadratic entropy, and presents example problems where the ITL framework can be successfully applied: dynamic modelling, equalization, independent component analysis and cluster analysis.

Published
08-04-2016
How to Cite
Silva, D., Fantinato, D., Canuto, J., Duarte, L., Neves, A., Suyama, R., Montalvão, J., & Attux, R. (2016). An Introduction to Information Theoretic Learning, Part II: Applications. Journal of Communication and Information Systems, 31(1). https://doi.org/10.14209/jcis.2016.7
Section
Tutorial Papers