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Image Processing using Pulse-Coupled Neural Networks pp 11–19Cite as

PCNN Theory

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Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

Abstract

The Pulse-Coupled Neural Network is to a very large extent based on the Eckhorn model except for a few minor modifications required by digitisation. The early experiments demonstrated that the PCNN could process images such that the PCNN output was quite similar for images that were shifted, rotated, scaled, and skewed. Subsequent investigations determined the basis of the working mechanisms of the PCNN and led to its eventual usefulness as an image-processing engine.

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Author information

Authors and Affiliations

  1. Department of Physics, Royal Institute of Technology, 24 Frescativagen, S-104 05, Stockholm, Sweden

    Thomas Lindblad PhD

  2. The Institute for Biosciences, Bioinformatics and Biotechnology, MSN 4E3, George Mason University, 10900 University Boulevard, Manassas, VA, 20100, USA

    Jason M. Kinser DSc

Authors
  1. Thomas Lindblad PhD
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  2. Jason M. Kinser DSc
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© 1998 Springer-Verlag London

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Lindblad, T., Kinser, J.M. (1998). PCNN Theory. In: Image Processing using Pulse-Coupled Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3617-0_2

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  • DOI: https://doi.org/10.1007/978-1-4471-3617-0_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76264-5

  • Online ISBN: 978-1-4471-3617-0

  • eBook Packages: Springer Book Archive

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