Multi-branch neural networks with branch control

Takashi Yamashita*, Kotaro Hirasawa, Jinglu Hu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Multi-branch neural networks have been proposed already in order to realize compact networks. It uses some branches between nodes, and this can improve the learning and generalization ability of the networks. In this paper, Branch Control is proposed on the multi-branch neural networks to further enhance the learning and generalization ability of the networks. Branch Control is to adjust the values of the signals on the branches depending on the network inputs using an additional branch control network. It has been clarified from simulation results of a function approximation problem that multi-branch neural networks with Branch Control could be improved more than that without Branch Control.

Original languageEnglish
Pages (from-to)756-761
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 2003 Nov 24
EventSystem Security and Assurance - Washington, DC, United States
Duration: 2003 Oct 52003 Oct 8


  • Functional localization
  • Multi-branch
  • Neural networks

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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