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Man-Machine Interactions 3 pp 257–263Cite as

An Application of Fuzzy C-Regression Models to Characteristic Point Detection in Biomedical Signals

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 242))

Abstract

This work introduces a new fuzzy c-regression models with various loss functions. The algorithm consists in solving a sequence of weighted quadratic minimization problems where the weights used for the next iteration depend on values of models residuals for the current iteration. Simulations on real-life ECG signals are realized to evaluate the performance of the fuzzy clustering method.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Alina Momot

  2. Institute of Medical Technology and Equipment, Roosevelt 118, 41-800, Zabrze, Poland

    Michal Momot & Jacek M. Leski

  3. Institute of Electronics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Jacek M. Leski

Authors
  1. Alina Momot
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  2. Michal Momot
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  3. Jacek M. Leski
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Corresponding author

Correspondence to Alina Momot .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dr. Aleksandra Gruca

  2. Polish Academy of Sciences and Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

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© 2014 Springer International Publishing Switzerland

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Momot, A., Momot, M., Leski, J.M. (2014). An Application of Fuzzy C-Regression Models to Characteristic Point Detection in Biomedical Signals. In: Gruca, D., Czachórski, T., Kozielski, S. (eds) Man-Machine Interactions 3. Advances in Intelligent Systems and Computing, vol 242. Springer, Cham. https://doi.org/10.1007/978-3-319-02309-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-02309-0_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02308-3

  • Online ISBN: 978-3-319-02309-0

  • eBook Packages: EngineeringEngineering (R0)

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