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本文提出了基于复数U - D分解的复参数最小二乘估计方法。
The Paper presents a new U-D factorization based least squares methods for complex estimation.
本文主要讨论了线性流形上复对称矩阵的最小二乘问题。
This paper mainly discusses the least squares problem of complex symmetric matrices on a linear manifold.
当平差模型中存在复共线关系时，未知参数的最小二乘估计很不可靠。
The least Square estimates are not reliable when there exists multicollinearity in adjustment model.
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