Yang Zi-jiang | Faculty Of Engineering Kyushu University
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概要
関連著者
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Yang Zi-jiang
Faculty Of Engineering Kyushu University
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Yang Zi-jiang
Faculty Of Information Science And Electrical Eng. Kyushu Univ.
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WADA Kiyoshi
Faculty of Information Science and Electrical Eng.,Kyushu Univ.
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Yang Z‐j
Kyushu Univ.
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Yang Zi-jiang
Graduate School Of Information Science And Electrical Engineering Kyushu University
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KANAE Shunshoku
Graduate school of information science and electrical engineering, Kyushu University
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Jia Li-juan
Dept.of Electrical And Electronic Systems Eng. Graduate School Of Information Science And Electrical
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Yang Z‐j
Graduate School Of Information Science And Electrical Engineering Kyushu University
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Yang Zi‐jiang
Kyushu Univ.
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BAE Chul-Min
Dept.of Electrical and Electronic Systems Eng.,Faculty of Information Science and Electrical Eng.,Ky
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Jin C‐z
Kyushu Univ.
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Bae Chul-min
Dept.of Electrical And Electronic Systems Eng. Faculty Of Information Science And Electrical Eng. Ky
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JIN Chun-Zhi
Dept.of Electrical and Electronic Systems Eng.,Faculty of Information Science and Electrical Eng.,Ky
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Jin Chun-zhi
Dept.of Elecrical And Electronic Systems Eng. Graduate School Of Information Science And Electrical
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Kanae Shunshoku
Kyushu Univ.
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Kanae Shunshoku
Graduate School Of Information Science And Electrical Engineering Kyushu University
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DACHAPAK Chooleewan
Dept.of Electrical and Electronic Systems Eng.,Graduate School of Information Science and Electrical
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KANAE Shunshoku
Faculty of Information Science and Electrical Eng.of Kyushu Univ.
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Dachapak Chooleewan
Department Of Electrical And Electronic Systems Engineering Graduate School Of Information Science A
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Sagara Setsuo
Faculty Of Engineering Kyushu University
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Wada Kiyosi
Faculty of Engineering, Kyushu University
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Yang Zi
Faculty of Information Science and Electrical Eng.,Kyushu Univ.
著作論文
- Parameter Estimation of Orthonormal Functions Using Block Toeplitz Construction
- On Parameter Estimation of Autoregressive Process in the Presence of Noise
- Kernel Principal Component Regression with Application to Nonlinear Prediction
- Parameter Identification Based on the Steiglitz-McBride Method from Noisy Input-Output Data