Comparisons of Seven Neural Network Models on Traffic Control Problems in Multistage Interconnection Networks

Nobuo Funabiki; Yoshiyasu Takefuji; Kuo Chun Lee

doi:10.1109/12.214695

Comparisons of Seven Neural Network Models on Traffic Control Problems in Multistage Interconnection Networks

Nobuo Funabiki
, Yoshiyasu Takefuji
, Kuo Chun Lee

研究成果: Article › 査読

15 被引用数 (Scopus)

抄録

This paper presents performance comparisons of seven neural network models on traffic control problems in multistage interconnection networks. The decay term, three neuron models, and two heuristics were evaluated. The goal of the traffic control problems is to find conflict-free switching configurations with the maximum throughput. Our simulation results show that the hysteresis McCulloch-Pitts neuron model without the decay term and with two heuristics has the best performance.

本文言語	English
ページ（範囲）	497-501
ページ数	5
ジャーナル	IEEE Transactions on Computers
巻	42
号	4
DOI	https://doi.org/10.1109/12.214695
出版ステータス	Published - 1993 4月
外部発表	はい

ASJC Scopus subject areas

ソフトウェア
理論的コンピュータサイエンス
ハードウェアとアーキテクチャ
計算理論と計算数学

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10.1109/12.214695

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Comparisons of Seven Neural Network Models on Traffic Control Problems in Multistage Interconnection Networks

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