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Diffusion approximation on neural networks and applications for image processing

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Part of the book series: European Consortium for Mathematics in Industry ((XECMI))

Abstract

We derive reaction-diffusion approximations for simple models of neural networks. On the basis of this formal link we construct a non linear diffusion operator which combined with reaction allows to obtain non trivial asymptotic states. The efficiency of this model in terms of image processing is discussed on test images as well as medical images.

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References

  1. Berthomier, F. and al. ‘Asymptotic behavior of neural networks and image processing’, in A. Babloyantz (ed), Self-organization, Emerging properties and learning, Plenum Press, NATO Series (to appear).

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  2. Cottet, G.-H. (1991) ‘Modèles de reaction-diffusion pour des réseaux de neurones stochastiques et déterministes ’, C. R. Acad. Sci. Paris, 312, 217–221.

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  3. Cottet, G.-H. and Germain, L. (1992) ‘Non-linear diffusion combined to reaction for image processing ’, preprint.

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  4. De Masi, A. and al. (1986) ‘Reaction-diffusion equations for interacting particle systems’, Journal of Stat. Phys., 44, 589–627.

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  5. François, O. (1992) Thèse de l’Université Joseph Fourier, Grenoble

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  6. Hopfield, J. J. (1984) ‘Neurons with graded response have collective computational properties like those of two-states neurons’, Proc. Natl. Acad. Sci., 81, 3088–3092.

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  7. Alvarez, L. and al (1991) ‘Image selective smoothing by nonlinear diffusion’, preprint.

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© 1992 Springer Fachmedien Wiesbaden

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Cottet, GH. (1992). Diffusion approximation on neural networks and applications for image processing. In: Hodnett, F. (eds) Proceedings of the Sixth European Conference on Mathematics in Industry August 27–31, 1991 Limerick. European Consortium for Mathematics in Industry. Vieweg+Teubner Verlag, Wiesbaden. https://doi.org/10.1007/978-3-663-09834-8_1

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  • DOI: https://doi.org/10.1007/978-3-663-09834-8_1

  • Publisher Name: Vieweg+Teubner Verlag, Wiesbaden

  • Print ISBN: 978-3-663-09835-5

  • Online ISBN: 978-3-663-09834-8

  • eBook Packages: Springer Book Archive

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