本文提出了利用关联矩阵进行查询分解优化的具体过程和算法。这种方法极利于在计算机上实现。
The actual procedure and algorithm for query decomposition optimisation with association matrix is proposed, and is convenient to be performed on a computer.
利用矩阵的极分解，导出了逆特征值问题的最佳逼近解。
The optimal approximate solution of this inverse eigenvalue problem also was given by means of the polar decomposition of matrices.
通过对方向矩阵进行极分解构造聚焦矩阵，把各个窄带频率处的信号子空间变换到聚焦频率处的信号子空间。
Focus matrix is constructed by polar decomposition of location matrix and transforms signal subspace at different frequency bins to signal subspace at focusing frequency bin.
本文主要研究有关矩阵的加权广义逆，加权极分解和矩阵偏序等方面的问题。
In this thesis, we mainly study problems on weighted generalized inverses, weighted polar decomposition, and partial orderings of matrices.
本文主要研究有关矩阵的加权广义逆，加权极分解和矩阵偏序等方面的问题。
In this thesis, we mainly study problems on weighted generalized inverses, weighted polar decomposition, and partial orderings of matrices.
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