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24 th. EUROMICRO Conference Volume 2 (EUROMICRO'98)
FPGA Based Implementation of a Hopfield Neural Network for Solving Constraint Satisfaction Problems
Västerås, Sweden
August 25-August 27
ISBN: 0-8186-8646-4
David Abramson, Monash University
Kate Smith, Monash University
Paul Logothetis, Monash University
David Duke, Monash University
This paper discusses the implementation of Hopfield neural networks for solving constraint satisfaction problems using Field Programmable Gate Arrays (FPGAs). It discusses techniques for formulating such problems as discrete neural networks, and then it describes the N-Queen problem using this formulation. A prototype implementation of the a number of different N-Queen problems is described and results are presented that illustrate that a speedup of up to 3 orders of magnitude is possible using current FPGAs devices
Citation:
David Abramson, Kate Smith, Paul Logothetis, David Duke, "FPGA Based Implementation of a Hopfield Neural Network for Solving Constraint Satisfaction Problems," euromicro, vol. 2, pp.20688, 24 th. EUROMICRO Conference Volume 2 (EUROMICRO'98), 1998
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