The direct form for the recursive least squares estimation via matrix QR decomposition with one step data updated is given .

给出了当数据一步更新时，利用矩阵QR分解进行最小二乘估计的直接递推形式。

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Based on this point, this paper proposes a new task partition scheme for matrix QR decomposition, and a new coarse granularity parallel algorithm is given.

基于这一点，本文对矩阵的QR分解提出了一种新的任务划分策略，并由此得到了它的一种粗粒度并行算法。

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In this paper, by using the special structure of the covariance matrix, a fast high resolution method based on QR decomposition is presented.

利用阵列输出协方差矩阵的特殊结构，本文提出一种基于QR分解的高分辨谱估计方法及其改进形式。

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