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

Yuen Hsien Tseng, Ja Ling Wu

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)601-604
Number of pages4
JournalIEEE Transactions on Computers
Volume44
Issue number4
DOIs
Publication statusPublished - 1995 Apr

Keywords

  • Quadratic perceptron
  • complexity
  • nonbinary majority
  • sorting
  • winner-take-all

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'On a Constant-Time, Low-Complexity Winner-Take-All Neural Network'. Together they form a unique fingerprint.

Cite this