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WaRS: A Method for Signal Classification

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Book cover Rough-Neural Computing

Part of the book series: Cognitive Technologies ((COGTECH))

Summary

Rough hybrid methods are used worldwide for pattern recognition and classification problems. In this chapter, WaRS, a combination of wavelets with rough set tools is presented, and examples of its application to problems of artificial and real-life (biomedical) origin are supplied.

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Author information

Authors and Affiliations

  1. Department of Mechanical and Aeronautical Engineering, University of California, One Shields Avenue, Davis, CA, 95616, USA

    Piotr Wojdyłło

Authors
  1. Piotr Wojdyłło
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Machine Intelligence Unit, 203 Barrackpore Trunk Road, Calcutta, 700 035, India

    Sankar K. Pal

  2. Department of Mathematics and Computer Science, University of Warmia and Mazury, Zolnierska 14, Olsztyn, Poland

    Lech Polkowski

  3. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2004 Springer-Verlag Berlin Heidelberg

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Wojdyłło, P. (2004). WaRS: A Method for Signal Classification. In: Pal, S.K., Polkowski, L., Skowron, A. (eds) Rough-Neural Computing. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18859-6_27

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  • DOI: https://doi.org/10.1007/978-3-642-18859-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-62328-8

  • Online ISBN: 978-3-642-18859-6

  • eBook Packages: Springer Book Archive

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