根据矩阵谱分解的思想，提出多点任意相关的随机载荷识别方法。
The identification of multi-point arbitrary correlated stationary random load is presented in the paper in the light of the method of matrices spectrum decomposition.
可逆的向量滑动平均(MA)模型参数估计问题本质上是一个矩阵谱分解问题。
The parameter estimation problem to the invertible vector moving average (ma) model essentially is a matrix spectral factorization problem.
考虑含有两个方差分量矩阵的多元混合模型，将一元混合模型下的谱分解估计推广到多元模型下。
Spectral decomposition estimators of variance component matrix in mixed linear model are generalized to multivariate mixed linear model.
为实现矩阵快速求逆，文中采用了螺旋边界条件下谱因式分解的方法。
Fortunately, however, the matrix has striped shape with a helical boundary conditions.
给出实矩阵的广义谱分解式，讨论广义正定实矩阵的特征根的一些性质。
In this paper, we give a general spectral resolution of real matrix and some properties eigenvalue of a general positive definite real matrix.
给出实矩阵的广义谱分解式，讨论广义正定实矩阵的特征根的一些性质。
In this paper, we give a general spectral resolution of real matrix and some properties eigenvalue of a general positive definite real matrix.
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