A new K-winners-take-all neural network

Shubao Liu, Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

In this paper, the K-Winners-Take-All (KWTA) operation is converted to an equivalent constrained convex quadratic optimization formulation. A simplified dual neural network, called KWTA network, is further developed for solving the convex quadratic programming (QP) problem. The KWTA network is shown to be globally convergent to the exact optimal solution of the QP problem. Simulation results are presented to show the effectiveness and performance of the KWTA network.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks, IJCNN 2005
Pages712-716
Number of pages5
DOIs
Publication statusPublished - 2005
Externally publishedYes
EventInternational Joint Conference on Neural Networks, IJCNN 2005 - Montreal, QC, Canada
Duration: 31 Jul 20054 Aug 2005

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2

Conference

ConferenceInternational Joint Conference on Neural Networks, IJCNN 2005
Country/TerritoryCanada
CityMontreal, QC
Period31/07/054/08/05

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