FPGA based implementation of a Hopfield neural network for solving constraint satisfaction problems

被引：0

作者：

Abramson, D ^{[1
]}

Smith, K ^{[1
]}

Logothetis, P ^{[1
]}

Duke, D ^{[1
]}

机构：

[1] Monash Univ, Sch Comp Sci & Software Engn, Clayton, Vic 3168, Australia

来源：

24TH EUROMICRO CONFERENCE - PROCEEDING, VOLS 1 AND 2 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：688 / 693

页数：2

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