書誌事項
- タイトル別名
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- Multi-Branch Structure and its Localized Property in Layered Neural Networks
- カイソウガタ ニューラル ネットワーク ニ オケル マルチブランチ コウゾウ ト ソノ キョクショセイ
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Neural networks (NNs) can solve only a simple problem if the network size is too small, on the other hand, if the network size increases, it costs a lot in terms of memory space and calculation time. So, we have studied how to construct the network structure with high performances and low costs in space and time. A solution is a multi-branch structure. Conventional NNs use the single-branch for the connections, while the multi-branch structure has multi-branches between nodes. In this paper, a new method which enables the multi-branch NNs to have localized property is proposed. It is well known that RBF networks have localized property that makes it possible to approximate functions faster than sigmoidal NNs. By using the multi-branch structure having localized property of RBF networks, NNs could obtain high performances keeping the lower costs in space and time. Simulation results of function approximations and a classification problem illustrated the effectiveness of multi-branch NNs.
収録刊行物
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- 電気学会論文誌Ｃ（電子・情報・システム部門誌）
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電気学会論文誌Ｃ（電子・情報・システム部門誌） 125 (6), 941-947, 2005
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204606257024
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- NII論文ID
- 10015672231
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 7387835
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
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- 抄録ライセンスフラグ
- 使用不可