Overlapped multi-neural-network: A case study

Jinglu Hu*, Kotaro Hirasawa

*この研究の対応する著者

研究成果査読

2 被引用数 (Scopus)

抄録

This paper presents a case study for the overlapped multi-neural-network (OMNN). An overlapped multi-neural-network, structurally, is the same as an ordinary feedforward neural network, but it is considered as one consisting of several subnets. All subnets have the same input-output units, but some different hidden units. Input-output spaces are partitioned into several parts, each of which corresponds to one subnet of OMNN. Numerical simulations show that such an OMNN has superior performance in that it has better presentation ability than an ordinary neural network and better generalization ability than a non-overlapped multi-neural-network.

本文言語English
ページ120-125
ページ数6
出版ステータスPublished - 2000 1 1
外部発表はい
イベントInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
継続期間: 2000 7 242000 7 27

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period00/7/2400/7/27

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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