未知な変動パラメータを含むウイナーシステムの同定 Identification of Time-Varying Wiener Systems with Unknown Parameters

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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.

収録刊行物

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society  

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 128(7), 1102-1109, 2008-07-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10021133086
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    9564168
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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