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Multi-valued and Universal Binary Neurons: New Applications in Intelligent Image Processing

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Computational Intelligence. Theory and Applications (Fuzzy Days 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

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Abstract

Multi-valued neurons (MVN) and universal binary neurons (UBN) are neural elements with complex-valued weights and high functionality. It is possible to implement the arbitrary mapping described by partially defined multiple-valued function on the single MVN and the arbitrary mapping described by Boolean function (which may not be threshold) on the single UBN. In this paper we consider some applications carried out using these wonderful features of MVN and UBN. Conception of cellular neural networks based on MVN and UBN becomes a base for nonlinear cellular neural filtering. Application of the corresponding filters for edge detection and solving of the super-resolution problem are considered in the paper.

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Authors and Affiliations

  1. Neural Networks Technologies (NNT) Ltd., 155 Bialik st., Ramat-Gan, 52523, Israel

    Igor Aizenberg

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  1. Igor Aizenberg
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Editor information

Editors and Affiliations

  1. Computer Science I, University of Dortmund, 44221, Dortmund, Germany

    Bernd Reusch

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© 2001 Springer-Verlag Berlin Heidelberg

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Aizenberg, I. (2001). Multi-valued and Universal Binary Neurons: New Applications in Intelligent Image Processing. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_46

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  • DOI: https://doi.org/10.1007/3-540-45493-4_46

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

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