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System Classification by Using Discriminant Functions of Time-Frequency Features

  • Miguel Mendoza Reyes
  • Juan V. Lorenzo-Ginori
  • A. Taboada-Crispí
  • Yakelin Luna Carvajal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)

Abstract

Time-frequency representations (TFR) convey relevant information about systems that can not be obtained under stationary conditions. In this paper, a methodology to classify systems using the information obtained from time-frequency representations during transient phenomena is described and tested experimentally. The study includes an assessment of the features to be extracted from the TFR, which are relevant for the desired classification, as well as the construction of the appropriate discriminant functions using them. The methodology is tested by means of a biomedical example related to patient’s classification.

Keywords

time-frequency distributions feature extraction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Miguel Mendoza Reyes
    • 1
  • Juan V. Lorenzo-Ginori
    • 1
  • A. Taboada-Crispí
    • 1
  • Yakelin Luna Carvajal
    • 2
  1. 1.Center for Studies on Electronics and Information TechnologiesUniversidad Central “Marta Abreu” de Las VillasSanta ClaraCuba, USA
  2. 2.Ministry of Public HealthSanta ClaraCuba

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