Blind Identification of Multichannel Systems by Scalar-Valued Linear Prediction

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概要

• 論文の詳細を見る

• An algorithm for blind identification of multichannel (single-input and multiple-output) FIR systems is proposed. The proposed algorithm is based on subspace approach to blind identification, which requires so-called noise space spanned by some eigenvectors of correlation matrices of observations. It is shown that a subspace of the noise space can be obtained by one-step scalar-valued linear prediction and then the subspace is sufficient for blind identification. To acquire the subspace, the proposed algorithm utilizes one-step scalar-valued linear prediction in place of a singular- (or eigen-) value decomposition and hence it is computationally efficient. Computer simulations are presented to compare the proposed algorithm with the original one.

• 社団法人電子情報通信学会の論文
• 2001-08-01

著者

• Ohno Shuichi

  The Author Is With The Department Of Mathematics And Computer Science Shimane University

• SAKAI Hideaki

  The author is with the Department of Systems Science, Graduate School of Informatics, Kyoto Universi

• Sakai Hideaki

  The Author Is With The Department Of Systems Science Graduate School Of Informatics Kyoto University

関連論文

• Blind Identification of Multichannel Systems by Scalar-Valued Linear Prediction

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