Nonlinear System Identification Using Probabilistic Universal Learning Networks
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- Hirasawa Kotaro
- Kyushu University
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- Yotsumoto Kazuaki
- Kyushu University
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- Hu Jinglu
- Kyushu University
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- Yu Yunqing
- Kyushu University
Bibliographic Information
- Other Title
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- 確率一般化学習ネットワークによる非線形動的システムの同定
- カクリツ イッパンカ ガクシュウ ネットワーク ニ ヨル ヒセンケイ ドウテキ システム ノ ドウテイ
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Abstract
Probabilistic Universal Learning Networks are proposed, where a calculation method of the propagation of stochastic signals through Universal Learning Networks is provided. Probabilistic Universal Learning Networks also provide a gradient learning method to optimize parameters in Universal Learning Networks by minimizing the value of the stochastic-based evaluation function. From simulations, it has been shown that identification of a nonlinear dynamic system can be realized without overfitting by using Probabilistic Universal Learning Networks.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 120 (10), 1380-1387, 2000
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390282679588765056
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- NII Article ID
- 130006846125
- 10005315425
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 5505603
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed