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

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Abstract

The PCNN convolution kernel is one of the main components of the PCNN. It can be manipulated to provide a variety of computations. The original Eckhorn model used a Gaussian type of interconnections, but when the PCNN is applied to image processing problems these interconnections are available to the user for altering the behaviour of the network.

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References

  1. E. Neibur, F. Wörgötter, Circular Inhibition: A New Concept in Long-Range Interaction in the Mammalian Visual Cortex, Proc. IJCNN v. II, San Diego, 367–372 (1990).

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© 1998 Springer-Verlag London

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Lindblad, T., Kinser, J.M. (1998). The PCNN Kernel. In: Image Processing using Pulse-Coupled Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3617-0_4

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  • DOI: https://doi.org/10.1007/978-1-4471-3617-0_4

  • 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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