奇异值是矩阵的一个良好特征。
介绍了奇异值分解法的原理；
并行LanczosSVD(奇异值分解)计算。
本文使用奇异值分解法求解矩阵方程的最小二乘解。
A least squares solution via singular value decomposition is used to solve the matrix equation.
然后用奇异值分解给出了求解最小范数解的一种方法。
Then, a method is presented based on the singular value decomposition to compute the minimal norm solution.
采用阻尼最小二乘法与奇异值分解的方法来求解失调量。
By means of the damp least square method and singular value decomposition method, the misalignment of optical system could be calculated.
利用奇异值分解技术确定了定量度量模态可控程度的方法。
Using the singular value decomposition technique, the method for measuring the modal controllability is determined.
结果表明，使用奇异值解法能够明显提高频时域法的识别精度。
Assessment results show that the SVD technique can obviously improve identification accuracy as compared to the PI solution.
提出了一种结合奇异值分解（SVD）和DCT变换的零水印算法。
The paper brings forward a kind of hybrid SVD-DCT zero-watermark algorithm.
利用奇异值理论提取包含矩阵的奇异值作为气缸爆发噪声信号的特征。
Singular value is extracted as to feature of cylinder explosive noise signal from Cover Matrix with singular value theory.
研制的最小平方共轭梯度算法和奇异值分解法也可进行同样的层析反演。
The least square conjugate gradient and odd values decomposition method also can be used to perform tomographic inversion.
最小奇异值作为静态电压稳定指标已广泛应用于电力系统的稳定分析之中。
As an index of static voltage stability the minimum singular value is widely used in power system stability analysis.
子空间系统辨识方法确定系统的阶次是由可观测矩阵的非零奇异值来决定。
The system order is decided by non-zerosingular values of the observation matrix in the subspace state space systemidentification method.
利用矩阵的奇异值分解和矩阵分块方法，得到了最小二乘解的一般表达式。
By using the method of matrix singular values decomposition, the general expressions of the least squares solutions are given.
给出了一种基于矩阵奇异值分解(SVD)和奇异值量化的信息隐藏算法。
An algorithm based on singular value decomposition (SVD) is proposed, which hides secret information in singular value vector.
将奇异值分解同自然正交分解相结合，提出一种改进的正交奇异值分解方法。
An improved SVD method was introduced by combining empirical orthogonal function (EOF) with singular value decomposition (SVD).
用矩阵的奇异值分解和广义逆讨论标准线性规划问题解的存在性和唯一性问题。
Apply singular value decomposition and generalize inverse of the matrix to discuss the existence and uniqueness of the solution of the standard linear programming problem.
最后将新方法与回差矩阵最小奇异值方法进行了比较，验证了该方法的优越性。
Finally, the results are compared with return difference matrix method to illustrate the efficiency of the new method.
本文从探测奇异值的一般方法入手，探讨了四种典型方法的基本思想以及优缺点。
This paper discusses four basic approaches of detecting outliers, summarizes their main ideas and evaluates their strengths and weaknesses.
本文以对观测数据矩阵直接进行奇异值分解为基础提出了一种正弦检测的新方法。
A new method for sinusoidal detection is presented based on the SVD of the observation data matrix.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
本文对四元数体上矩阵奇异值摄动定理给出了推广，且这些结果对复矩阵也是新的。
The quaternion matrix singular value perturbation theorem is generalized and these results are also new one for complex matrix.
提出了基于小波包变换和改进奇异值分解的高分辨雷达目标一维距离像特征提取方法。
A feature extraction method of high-range-resolution radar profiles, which takes advantage of wavelet packet transform and modified SVD (singular value decomposition) was proposed.
利用结构奇异值理论将颤振理论模型和试飞数据有机结合起来，进行了颤振边界预测。
It incorporates organically the flight test data and the flutter theory model by the structured singular value theories, to process the flutter boundary estimate.
讨论了最小奇异值表示的电压稳定裕度指标和物理量表示的电压稳定裕度指标间的关系；
The relation between the voltage margin index expressed by minimum singular value and the voltage margin expressed by physical quantity is dis-cussed.
并利用奇异值分解方法和模矩阵的性质，给出了使不确定广义系统鲁棒稳定的一个鲁棒界。
A robust stability boundary of uncertain singular systems is proposed by utilizing singular value decomposition and the character of mode matrix.
结果表明，在设计矩阵高度共线性时，用奇异值分解的迭代加细可以改进回归系数的估计。
Results show that iterative refinement using the SVD can improve regression coefficient estimates in the cases where the design matrix is highly collinear.
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.
推导了小波分析与奇异信号检测的之间的关系，并对某压力传感器的信号进行了奇异值的检测。
The relationship between wavelet analysis and singular signal detecting is deduced, and the example of a pressure sensor singular signal detecting is presented.
通过对图像进行奇异值分解，将一幅图像转换成只包含几个非零值的奇异值矩阵，实现图像压缩。
Digital image is transformed into singular value matrix that contains non-zero singular values by singular value decomposition (SVD), the image is compressed.
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