An hopfield network learning for minimum vertex cover problem

Xiaoming Chen*, Zheng Tang, Xinshun Xu, Songsong Li, Guangpu Xia, Ziliang Zong, Jiahai Wang

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

An algorithm for the minimum vertex cover problem based on HNN leaning is presented. The network phase performs gradient descent in state domain, and finds a set of states minimizing the HNN's energy. When the HNN gets stuck, the learning phase is performed to fill up the local minimum valley by modifying parameter in gradient ascent direction of the energy.

Original languageEnglish
Pages1829-1834
Number of pages6
StatePublished - 2004
EventSICE Annual Conference 2004 - Sapporo, Japan
Duration: 2004/08/042004/08/06

Conference

ConferenceSICE Annual Conference 2004
Country/TerritoryJapan
CitySapporo
Period2004/08/042004/08/06

Keywords

  • Gradient ascent learning
  • Hopfield neural network
  • Local minimum
  • Vertex cover

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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