结果表明，该类电路的唯一稳态，可以用分解矩阵的稳定性来决定。
The main results obtained in this paper show that the unique steady state of the nonlinear nonautonomous circuits can be determined by the stability of decomposed matrixes.
这种方法以矩阵分解为工具，结合平衡点的渐近稳定判据，用分解矩阵的稳定性决定平衡点的全局渐近稳定性。
This method takes the matrix resolving as a tool, combined with criterion of progressive stability and determines the equilibrium point by stability of matrix resolving.
所有矩阵通常都能以各种方式因式分解。
All matrices can be factorised, usually in a variety of ways.
最常见的数字信号处理技术之一是离散傅立叶变换（DFT），它把一个信号分解成它的组成频率，并表示成一个矩阵。
One of the most common digital-signal-processing techniques is the discrete Fourier transform (DFT), which breaks a signal into its component frequencies and can be represented as a matrix.
本文系统的研究了四元数矩阵分解理论。
In this paper, decomposition of a quaternion matrix is systemically studied.
利用协方差矩阵的特征值。能实现信号和噪声的分解。
The eigenvalue of covariance matrix can be used to separate signal from noise.
听起来像是一个经典的矩阵分解我的任务。
通过对相关矩阵进行特征值分解，估计信号子空间和噪声子空间，并利用MU S IC算法估计宽带LF M信号的波达方向。
Through estimating the signal and noise subspaces with the eigen-decomposition of the correlation matrix, the MUSIC algorithm is used to estimate the DOAs of LFM sources.
LU分解是一种将非奇异矩阵进行三角分解的方法，而数字图像也可以看作矩阵。
LU decomposition is a triangular decomposition approach of non-singular matrix, and the digital image can be seen as a matrix.
本文对用于DOA估计的矩阵分解法进行了分析，证明了它是一种子空间方法。
The matrix decomposition method for DOA estimation is analyzed. It is proved that the method is a subspace method.
该方法仅需进行一次系统矩阵的分解就可获得高精度的多个复振型导数。
Finally, many complex mode shape derivatives of high accuracy can be obtained by decomposing system matrices only once.
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.
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。
The direct form for the recursive least squares estimation via matrix QR decomposition with one step data updated is given .
在机动加速度“当前”统计自适应卡尔曼滤波算法的基础上，引入了基于Q - R矩阵分解的自适应卡尔曼滤波算法。
Based on the algorithm of maneuvering acceleration current statistical model adaptive filtering, the adaptive kalman filtering algorithm based on QR matrix decomposition is presented in this paper.
矩阵分解在很多领域获得了广泛的应用。
Matrix decomposition has been widely applied in many fields.
应注意在构造ARMA新息模型时，必须进行多项式矩阵的左素分解，才能得到正确的ARMA新息模型。
Notice that constructing the ARMA innovation model, a left co-prime factorization to a polynomial matrix must be performed, so that the ARMA innovation model can correctly be obtained.
对角矩阵及三角矩阵之特征值，相似矩阵，由QR分解计算特征值，主特征值之迭代估算。
Eigenvalues of diagonal and triangular matrices, similarity transforms, calculation of eigenvalues from QR decomposition, iteratively estimating the leading eigenvalue.
本文给出用特征矩阵分解与初等行变换求A的一系列幂的简捷方法。
This paper shows some simple methods to calculate the powers of A using the characteristic matrix decomposition and the elementary row operation.
QR分解可以改善矩阵条件数，从而提高数值稳定性。
QR decomposition can improve the condition number of a matrix and then improve the numerical stability.
标准子空间的扰动分析：本文给出了矩阵的酉分解中酉因子的最小扰动界。
Perturbation analysis of the canonical subspaces: This paper gives the least perturbation bound of the unitary factor on the unitary decomposition.
通过矩阵的初等变换可实现矩阵的满秩分解和强满秩矩阵的三角分解。
Full rank decomposition of matrix and triangular decomposition of strongly full rank can well be realized by elementary transformation method of matrix.
这类问题与矩阵函数因子分解有着密切联系。
The problems are closelurelated with factorization problems for rational matrix functions.
摘要研究了四元数矩阵分解为两个自共轭矩阵乘积，其中有一个是非奇异阵的条件，得到了一些有用的结果。
It is studied factorizing a matrix over quaternion field to the product of two self - conjugate matrices . and some useful results are obtained.
说明：矩阵LU分解的并行实现，文档中给出了不同矩阵规模和处理器数下的实验结果。
Matrix LU decomposition parallel implementation, the document gives a different matrix size and the number of processors under the experimental results.
非负矩阵分解具有非负性和局部性的特点，是一种新型的特征提取方法。
Non-negative matrix factorization has non-negative and local characteristics, and it is a new feature extraction method.
本文借助于非负矩阵分解算法，提出了一种基于非负因子分析的模糊文本聚类方法。
Inspired by the nonnegative matrix factorization algorithm, we put forward an fuzzy text clustering method based on nonnegative factor analysis.
矩阵分解是矩阵计算的重要工具。
Matrix decomposition is an important tool for matrix computation.
奇异值分解是将一矩阵分解为一个对角矩阵和两个正交矩阵，奇异值分解有着非常好的性质。
By decomposing a matrix into one diagonalizable matrix and two orthogonal matrixes, singular value decomposition has very good properties.
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.
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.
应用推荐