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International Work-Conference on Artificial Neural Networks

IWANN 1999: Foundations and Tools for Neural Modeling pp 152–162Cite as

Model of the neuronal net for detection of single bars and cross-like figures

  • Neural Modeling (Biophysical and Structural Models)
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1606))

Abstract

The model of the discrete net for detection of cross-like figures is offered. The properties of the simulated detector of cross are investigated and compared with real cross-detectors found in the cat primary visual cortex. It is shown that an excitatory convergence from some neurons with different preferred orientations and an amplifying mechanism is necessary for effective detection of a cross-like figure.

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References

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Author information

Author notes

  1. Prof. Igor A. Shevelev

    Present address: Department of Sensory Physiology, Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5-a Butlerova Street, 117865, Moscow, Russia

Authors and Affiliations

  1. Department of Sensory Physiology, Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5-a Butlerova Street, 117865, Moscow, Russia

    Konstantin A. Saltykov

Authors
  1. Konstantin A. Saltykov
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  2. Prof. Igor A. Shevelev
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Corresponding author

Correspondence to Igor A. Shevelev .

Editor information

José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Saltykov, K.A., Shevelev, I.A. (1999). Model of the neuronal net for detection of single bars and cross-like figures. In: Mira, J., Sánchez-Andrés, J.V. (eds) Foundations and Tools for Neural Modeling. IWANN 1999. Lecture Notes in Computer Science, vol 1606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0098169

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  • DOI: https://doi.org/10.1007/BFb0098169

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66069-9

  • Online ISBN: 978-3-540-48771-5

  • eBook Packages: Springer Book Archive

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