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Derivation of a fast algorithm of modified H∞filters
https://iwate-u.repo.nii.ac.jp/records/9668
https://iwate-u.repo.nii.ac.jp/records/96680a916c98-13f5-45ce-add6-053033808bb5
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
ies2000-v1p462-467.pdf (216.5 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||
|---|---|---|---|---|---|---|---|---|
| 公開日 | 2008-11-06 | |||||||
| タイトル | ||||||||
| タイトル | Derivation of a fast algorithm of modified H∞filters | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | H∞ filter | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | fast algorithm | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Kalman filter | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | robust estimation | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | system identification | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | LMS | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||
| 資源タイプ | journal article | |||||||
| 著者 |
NISHIYAMA, Kiyoshi
× NISHIYAMA, Kiyoshi
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| 著者(機関) | ||||||||
| 値 | Dep. of Comp. & Info. Science, Iwate University | |||||||
| 登録日 | ||||||||
| 日付 | 2008-11-06 | |||||||
| 書誌情報 |
Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE 巻 1, p. 462-467, 発行日 2000-01-01 |
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| ISBN | ||||||||
| 識別子タイプ | ISBN | |||||||
| 関連識別子 | 0-7803-6456-2 | |||||||
| Abstract | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | The fast Kalman filter provides very quick convergence at the computational complexity of the same order that the LMS algorithm requires. Nevertheless, its performance is still unsatisfactory in system identification because the conventional fast Kalman filter fails to track time-varying impulse responses of FIR systems. The failure of tracking is due to the absence of system noise in the state-space model to be used. However, according to the derivation of the fast Kalman filter, it is difficult to theoretically introduce the term of system noise into the algorithm. In the paper, to overcome the difficulties, a new fast filtering algorithm, called a fast H∞ filter, is derived based on the H∞ theory. | |||||||
| 出版者 | ||||||||
| 出版者 | IEEE | |||||||
| 権利 | ||||||||
| 権利情報 | ©2000 IEEE | |||||||
| DOI | ||||||||
| 識別子タイプ | DOI | |||||||
| 関連識別子 | 10.1109/IECON.2000.973194 | |||||||
