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Information Granules and Rough-Neural Computing

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Rough-Neural Computing

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

Summary

In this chapter we discuss the foundations of rough-neural computing (RNC). We introduce information granule systems and information granules in such systems. Information granule networks, called approximate reasoning schemes (AR schemes), are used to represent information granule constructions. We discuss the foundations of RNC using an analogy of information granule networks with neural networks. RNC is a basic paradigm of granular computing (GC). This paradigm makes it possible to tune AR schemes to construct relevant information granules, e.g., satisfying a given specification to a satisfactory degree. One of the goals of our project is to develop methods based on rough-neural computing for computing with words (CW).

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Author information

Authors and Affiliations

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

    Andrzej Skowron

  2. Department of Computer Science, Białystok University of Technology, Wiejska 45A, Białystok, 15-351, Poland

    Jarosław Stepaniuk

Authors
  1. Andrzej Skowron
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  2. Jarosław Stepaniuk
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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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Skowron, A., Stepaniuk, J. (2004). Information Granules and Rough-Neural Computing. 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_3

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  • DOI: https://doi.org/10.1007/978-3-642-18859-6_3

  • 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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