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IAF Neuron Implementation for Mixed-Signal PCNN Hardware

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Computational and Ambient Intelligence (IWANN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4507))

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Abstract

In this paper, the implementation results of an integrate and fire neuron implemented in a 130 nm process are presented. This publication covers the properties of IAF neurons from calculations on an ideal electrical circuit modeling the soma of an IAF neuron and compares the theoretical results with simulation results from an extracted layout of the implemented neuron.

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References

  1. Matolin, D., Schreiter, J., Getzlaff, S., Schüffny, R.: An Analog VLSI Pulsed Neural Network Implementation for Image Segmentation. In: Proc. of the International Conference on Parallel Computing in Electrical Engineering, pp. 51–55 (2004)

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Francisco Sandoval Alberto Prieto Joan Cabestany Manuel Graña

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© 2007 Springer-Verlag Berlin Heidelberg

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Kaulmann, T., Lütkemeier, S., Rückert, U. (2007). IAF Neuron Implementation for Mixed-Signal PCNN Hardware. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_55

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  • DOI: https://doi.org/10.1007/978-3-540-73007-1_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73006-4

  • Online ISBN: 978-3-540-73007-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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