Abstract
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 language | English |
|---|---|
| Pages (from-to) | 756-761 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 1 |
| Publication status | Published - 2003 Nov 24 |
| Event | System Security and Assurance - Washington, DC, United States Duration: 2003 Oct 5 → 2003 Oct 8 |
Keywords
- Functional localization
- Multi-branch
- Neural networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture