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Nonlinear Mappings with Cellular Neural Networks

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Current Topics in Artificial Intelligence (CAEPIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4177))

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Abstract

In this paper, a general technique for automatically defining multilayer Cellular Neural Networks to perform Chebyshev optimal piecewise linear approximations of nonlinear functions is proposed. First, a novel CNN cell output function is proposed. Its main goal is to control input and output dynamic ranges. Afterwards, this 2-layer CNN is further programmed to achieve generic piecewise Chevyshev polynomials that approximate a nonlinear function.

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Author information

Authors and Affiliations

  1. Dpto. Electrónica e Ing. Electromecánica, Escuela de Ingenierías Industriales, Universidad de Extremadura, Avda. de Elvas, s/n, 06071, Badajoz, Spain

    J. Álvaro Fernández-Muñoz & Miguel A. Jaramillo-Morán

  2. Laboratory for Electromagnetic and Electronic Systems (LEES), Massachusetts Institute of Technology, Room 10-171, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA

    Víctor M. Preciado-Díaz

Authors
  1. J. Álvaro Fernández-Muñoz
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  2. Víctor M. Preciado-Díaz
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  3. Miguel A. Jaramillo-Morán
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Editor information

Editors and Affiliations

  1. Dpto. de Ingeniería de la Información da las Comunicaciones, Universidad de Murcia, Campus de Espinardo, s/n., 30071, Murcia, Spain

    Roque Marín

  2. Universidad Politecnica de Valencia, (Spain)

    Eva Onaindía

  3. Dept. Electronics and Computer Science, University of Santiago de Compostela,  

    Alberto Bugarín

  4. Department of Life Sciences, Imperial College London, SW7 2AZ, London, UK

    José Santos

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© 2006 Springer-Verlag Berlin Heidelberg

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Fernández-Muñoz, J.Á., Preciado-Díaz, V.M., Jaramillo-Morán, M.A. (2006). Nonlinear Mappings with Cellular Neural Networks. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_37

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  • DOI: https://doi.org/10.1007/11881216_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45914-9

  • Online ISBN: 978-3-540-45915-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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