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A hardware implementation of CNNs based on Pulse Stream Techniques

  • Neural Nets Simulation, Emulation and Implementation
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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

Cellular Neural Networks (CNNs) represents a computational paradigm which has evolved to cover a very broad class of problems and applications. Different implementations of CNNs using digital and analog technologies can be found in the literature. In this paper, a new hardware implementation is proposed that uses Pulse Stream Techniques (PST). PST techniques allow the implementation of large arrays of CNNs with programmable synapses, combining the best of both, digital and analog worlds.

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Authors and Affiliations

  1. Dpto. de Ingeniería Electrónica Escuela Superior de Ingenieros, Avda. Reina Mercedes, s/n, 41012, Sevilla

    F. Colodro, A. Torralba, R. González & L. G. Franquelo

Authors
  1. F. Colodro
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  2. A. Torralba
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  3. R. González
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  4. L. G. Franquelo
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José Mira Roberto Moreno-Díaz Joan Cabestany

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© 1997 Springer-Verlag Berlin Heidelberg

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Colodro, F., Torralba, A., González, R., Franquelo, L.G. (1997). A hardware implementation of CNNs based on Pulse Stream Techniques. 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/BFb0032540

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  • DOI: https://doi.org/10.1007/BFb0032540

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  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

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