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A low-bit learning algorithm for digital multilayer neural networks applied to pattern recognition
http://hdl.handle.net/2297/6841
http://hdl.handle.net/2297/68412139a718-ef35-439e-a7f6-871f31d1e9cb
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-NAKAYAMA-K-1867.pdf (655.7 kB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||
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| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | A low-bit learning algorithm for digital multilayer neural networks applied to pattern recognition | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
Nakayama, Kenji
× Nakayama, Kenji× Katayama, Hiroshi |
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| 書誌情報 |
Proc. IEEE&INNS IJCNN'91, Sigapore p. 1867-1872, 発行日 1991-11-01 |
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| 出版者 | ||||||
| 出版者 | IEEE(Institute of Electrical and Electronics Engineers) | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | A new low-bit learning algorithm for digital multilayer neural networks applied to pattern recognition is proposed. The training can be carried out with a small number of bits. To make the neural network insensitive to noisy patterns, conditions to be satisfied by hidden layer outputs are discussed. Based on this, optimum targets are assigned to the hidden layers. Computer simulation demonstrated the efficiency of the proposed method. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
