誤差逆伝播学習法による自己組織化ロバスト主成分分析
広島大学大学院工学研究科研究報告 Volume 53 Issue 1
Page 1-4
published_at 2004-12
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| File | |
| Title ( jpn ) |
誤差逆伝播学習法による自己組織化ロバスト主成分分析
|
| Title ( eng ) |
Self-Organized Robust Principal Component Analysis by Back-Propagation Learning
|
| Creator |
Higuchi Isao
|
| Source Title |
広島大学大学院工学研究科研究報告
Graduate School of Engineering, Hiroshima University
|
| Volume | 53 |
| Issue | 1 |
| Start Page | 1 |
| End Page | 4 |
| Abstract |
The purpose of this study is the suggestion of a self-organized back-propagation algorithm for robust principal component analysis. The self-organizing algorithm that discriminates the influence of data automatically is applied to learning of a sandglass type neural network.
|
| Keywords |
robust principal component analysis
neural networks
back-propagation
self-organizing rule
|
| NDC |
Technology. Engineering [ 500 ]
|
| Language |
jpn
|
| Resource Type | departmental bulletin paper |
| Publisher |
広島大学大学院工学研究科
国立情報学研究所
|
| Date of Issued | 2004-12 |
| Publish Type | Version of Record |
| Access Rights | open access |
| Source Identifier |
[ISSN] 1347-7218
[NCID] AA11700032
|
