データ行列のSVDを用いたARMA過程の次数推定

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概要

• 論文の詳細を見る

• In many fields of digital signal processing such as acoustic echo path estimation, modeling of the unknown systems has been required. Since the selection of the model order is very important in such modeling, various methods of selection have already been proposed. However, the order estimation of the ARMA model is very difficult due to the noise of the observed data, even in the case of known input data. Since, in the presence of additive noise in the output data, traditional methods fail to select a reasonable order, we propose a new algorithm to overcome this problem. Our proposed algorithm for ARMA model order selection is based on singular value decomposition (SVD) and new criteria of threshold values for the smallest singular value of the noisy data matrix. In the simulation, we show that our proposed algorithm is very effective for obtaining an appropriate rank of the noisy data matrix. We also show the good performance of our algorithm for practical estimation of the room acoustic transfer function.

• 社団法人日本音響学会の論文

著者

• 永井 信夫

  Research Institute of Applied Electricity,Hokkaido University

• ヌリ モハマド

  Research Institute For Electronic Science Hokkaido University

• 三木 信弘

  Department of Electronic Engineering,Faculty of Engineering,Hokkaido University

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• データ行列のSVDを用いたARMA過程の次数推定

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