On a Constant-Time, Low-Complexity Winner-Take-All Neural Network

Yuen Hsien Tseng; Ja Ling Wu

doi:10.1109/12.376175

On a Constant-Time, Low-Complexity Winner-Take-All Neural Network

Yuen Hsien Tseng
, Ja Ling Wu

研究成果: 雜誌貢獻 › 期刊論文 › 同行評審

12 引文斯高帕斯（Scopus）

摘要

A nearly cost-optimal winner-take-all (WTA) neural network derived from a constant-time sorting network is presented. The resultant WTA network has connection complexity [formula omitted] where s is the depth of cascaded sorting networks. Application of the WTA network to other problems such as nonbinary majority is also included.

原文	英語
頁（從 - 到）	601-604
頁數	4
期刊	IEEE Transactions on Computers
卷	44
發行號	4
DOIs	https://doi.org/10.1109/12.376175
出版狀態	已發佈 - 1995 4月
對外發佈	是

ASJC Scopus subject areas

軟體
理論電腦科學
硬體和架構
計算機理論與數學

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10.1109/12.376175

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abstract = "A nearly cost-optimal winner-take-all (WTA) neural network derived from a constant-time sorting network is presented. The resultant WTA network has connection complexity [formula omitted] where s is the depth of cascaded sorting networks. Application of the WTA network to other problems such as nonbinary majority is also included.",

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On a Constant-Time, Low-Complexity Winner-Take-All Neural Network

摘要

ASJC Scopus subject areas

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