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Design and fpga implementation of an embedded real-time biologically plausible spiking neural network processor

Authors :
Mokhtar Nibouche
Martin J. Pearson
L. Gilhesphy
Chris Melhuish
Kevin Gurney
Ben Mitchinson
Anthony G. Pipe
Source :
FPL
Publication Year :
2005
Publisher :
IEEE, 2005.

Abstract

The implementation of a large scale, leaky-integrate-and-fire neural network processor using the Xilinx Virtex-II family of field programmable gate array (FPGA) is presented. The processor has been designed to model biologically plausible networks of spiking neurons in real-time to assist with the control of a mobile robot. The real-time constraint has led to a re-evaluation of some of the established architectural and algorithmic features of previous spiking neural network based hardware. The design was coded and simulated using Handel-C hardware description language (HDL) and the DK3 design suite from Celoxica. The processor has been physically implemented and tested on a RC200 development board, also from Celoxica.

Details

Database :
OpenAIRE
Journal :
International Conference on Field Programmable Logic and Applications, 2005.
Accession number :
edsair.doi...........6d9500c3a045d862820402e40c727e35
Full Text :
https://doi.org/10.1109/fpl.2005.1515790