Two k-winners-take-all networks with discontinuous activation functions

Qingshan Liu, Jun Wang

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)

Abstract

This paper presents two k-winners-take-all (k-WTA) networks with discontinuous activation functions. The k-WTA operation is first converted equivalently into linear and quadratic programming problems. Then two k-winners-take-all networks are designed based on the linear and quadratic programming formulations. The networks are theoretically guaranteed to be capable of performing the k-WTA operation in real time. Simulation results show the effectiveness and performance of the networks.

Original languageEnglish
Pages (from-to)406-413
Number of pages8
JournalNeural Networks
Volume21
Issue number2-3
DOIs
Publication statusPublished - Mar 2008
Externally publishedYes

Keywords

  • Differential inclusion
  • Discontinuous activation function
  • Global convergence
  • Linear programming
  • Lyapunov stability
  • Quadratic programming
  • Recurrent neural network

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