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Generic neural network model and simulation toolkit

  • Formal Tools and Computational Models of Neurons and Neural Net Architectures
  • Conference paper
  • First Online:
Biological and Artificial Computation: From Neuroscience to Technology (IWANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

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Abstract

This work presents a generic higher-order model of neuron behaviour, connection scheme and learning rule, suited for high-speed parallel processing. In contrast to the construction of a real application, it would be more operational to expend effort in parameterizing the problem-solving architecture, offering a testbed as a useful simulation tool for experimenting with a variety of network designs within the said generic model. We include some initial simulation results applied to image processing and pattern recognition tasks.

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Authors and Affiliations

  1. Departamento de Electrónica e Ingeniería Electromecánica, Universidad de Extremadura, Avda. de Elvas s/n., 06071, Badajoz, Spain

    Montserrat García del Valle, Carlos García-Orellana, Francisco J. López-Aligué & Isabel Acevedo-Sotoca

Authors
  1. Montserrat García del Valle
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  2. Carlos García-Orellana
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  3. Francisco J. López-Aligué
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  4. Isabel Acevedo-Sotoca
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Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

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© 1997 Springer-Verlag Berlin Heidelberg

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del Valle, M.G., García-Orellana, C., López-Aligué, F.J., Acevedo-Sotoca, I. (1997). Generic neural network model and simulation toolkit. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032489

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  • DOI: https://doi.org/10.1007/BFb0032489

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

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