Identification of Time-Varying Wiener Systems with Unknown Parameters
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- Kobayashi Yasuhide
- Graduate School of Information Sciences, Hiroshima City-University
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- Shiotani Yuzuru
- Graduate School of Information Sciences, Hiroshima City-University
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- Hikita Shinichi
- Graduate School of Information Sciences, Hiroshima City-University
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- Nomura Kazuya
- CORE Corporation Chu-Shikoku Company
Bibliographic Information
- Other Title
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- 未知な変動パラメータを含むウィナーシステムの同定
- ミチナ ヘンドウ パラメータ オ フクム ウィナー システム ノ ドウテイ
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Abstract
Wiener systems which consist of a dynamic linear block followed by a static nonlinear element have been used in numerous applications. In many cases, the system parameters are affected by changes in the environmental conditions. This paper describes a new approach to the on-line identification of time-varying Wiener systems. The time-varying linear parameters and the static nonlinear characteristics are estimated by the neural networks which can represent various nonlinear characteristics. The initial states of the linear model in each estimation window are not available in the Wiener systems. Thus, the initial states and the other system parameters are estimated simultaneously by the nonlinear optimization techniques. Furthermore, the optimal numbers of hidden units in the neural networks are determined by the minimum description length (MDL) criterion.<br>As the result of the simulation of this method, more accurate parameters can be obtained than the result without the estimation of initial states and MDL.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 128 (7), 1102-1109, 2008
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
- 1390001204605041536
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- NII Article ID
- 10021133086
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 9564168
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed