A K-winners-take-all neural network based on linear programming formulation

Shenshen Gu, Jun Wang

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

7 Citations (Scopus)

Abstract

In this paper, the K-Winners-Take-All (KWTA) problem is formulated equivalently to a linear program. A recurrent neural network for KWTA is then proposed for solving the linear programming problem. The KWTA network is globally convergent to the optimal solution of the KWTA problem. Simulation results are further presented to show the effectiveness and performance of the KWTA network.

Original languageEnglish
Title of host publicationThe 2007 International Joint Conference on Neural Networks, IJCNN 2007 Conference Proceedings
Pages37-40
Number of pages4
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 International Joint Conference on Neural Networks, IJCNN 2007 - Orlando, FL, United States
Duration: 12 Aug 200717 Aug 2007

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)1098-7576

Conference

Conference2007 International Joint Conference on Neural Networks, IJCNN 2007
Country/TerritoryUnited States
CityOrlando, FL
Period12/08/0717/08/07

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