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On-line Hebbian learning for spiking neurons: Architecture of the weight-unit of NESPINN

  • Ulrich Roth
  • Axel Jahnke
  • Heinrich Klar
Part VIII: Implementations
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1327)

Abstract

We present the implementation of on-line Hebbian learning for NESPINN, the Neurocomputer for the simulation of spiking neurons. In order to support various forms of Hebbian learning we developed a programmable weight unit for the NESPINN-system. On-line weight modifications are performed event-controlled in parallel to the computation of basic neuron functions. According to our VHDL-simulations, the system will offer a performance of up to 50 MCUPS.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Ulrich Roth
    • 1
  • Axel Jahnke
    • 1
  • Heinrich Klar
    • 1
  1. 1.Institut für MikroelektronikTechnische Universität BerlinBerlin

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