Universal Learning Network Theory
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- Hirasawa Kotaro
- Kyushu University
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- Obayashi Masanao
- Kyushu University
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- Fujita Hirofumi
- Kyushu University
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- Koga Masaru
- Kyushu University
Bibliographic Information
- Other Title
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- 一般化学習ネットワーク理論
- イッパンカ ガクシュウ ネットワーク リロン
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Abstract
In this papaer, Universal Learning Network(U.L.N.) is proposed, which can be used as a fundamntal tool in modeling and control of large-scale complicated systems such as economic, social and living systems as well as industrial plants.<br>The basic idea of U.L.N. is that most of the large scale complicated systems can be modeled by the network which consists of nonlinearly operated nodes and branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed as ordinary first order difference equations with one sampling time delay.<br>In this sense, U.L.N. is a natural extention of recurrent neural network. It is also shown from simulation results of nonlinear identification that U.L.N. with arbitrary time delays can model nonlinear systems more efficiently than recurrent neural network.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 116 (7), 794-801, 1996
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204608585856
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- NII Article ID
- 130006844208
- 10001786365
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 3985584
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed