论文信息 - RECURSIVE UPDATING OF ERROR COVARIANCE MATRIX IN SUBSPACE METHODS

RECURSIVE UPDATING OF ERROR COVARIANCE MATRIX IN SUBSPACE METHODS

Using a unified approach, recursive algorithms of the error covariance matrices in subspace methods are derived for the MOESP type of subspace methods. The proposed approach is based on the fact that the subspace extraction amounts to computing singular value decomposition of the Schur complement (SC) of the input submatrix in data product moments and the SC can be interpreted as the least squares residuals. The recursion of the error covariance matrix can be applied to derive recursive subspace identification algorithms.

Zi‐Jiang Yang | S. Kanae | K. Wada | Y. Takei | H. Nanto

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