奇异值

词组短语

singular value

与奇异值相关的网络例句 [注：此内容来源于网络，仅供参考]

By means of analyzing the noise error, it is proposed to use an algorithm of singular value decomposition total least squares to conduct the interharmonics estimation, namely taking the noise interference at both sides of the matrix equation into account simultaneously and solving the minimum norm problem by least square method under such condition. In the proposed algorithm by means of singular value decomposition of a new augmented matrix and by use of a simple and practical method to determine the number of principal singular value related to signal to noise ratio, the storage calculation of right singular matrix is performed, thus a more accurate frequency estimation of interharmonics can be obtained.

通过分析噪声误差，提出采用奇异值总体最小二乘(singular value decomposition total least squares，SVDTLS)算法进行间谐波频率估计，即同时考虑矩阵方程两边的噪声干扰，采用SVDTLS算法求解该情况下的最小范数解，通过对增广矩阵进行奇异值分解(singular value decomposition，SVD)，采用简单实用的与信噪比相关的主奇异值个数确定方法对分解的右奇异矩阵进行存储计算，得到了较精确的间谐波频率估计结果。

In order to find a stable approximate solution of linear compact operator equation, the article introduces general theories about ill-posed problems, it bases on spectral theory of self-adjiont compact operators and the singular value decomposition for compact operators, avails singular system to give expression of the solution, and explains ill-posedness of compact operator equation roots in the property that the singular values trends to zero. Thereout, it is provided with theoretic support of building up regularization method by inducting regularization filter to weaken or filtrate the influence that the nature of the singular value being very close to zero has on the solutions stability.

为了得到线性紧算子方程稳定的近似解，介绍了不适定问题正则化的一般理论，以自伴紧算子的谱分析与紧算子奇异值分解为理论基础，利用奇异系给出了解的表达式，说明了紧算子方程不适定性的根源在于紧算子的奇异值趋于零的性质，由此通过引入正则化滤子函数来减弱或滤掉奇异值趋于零的性质对解的稳定性的影响，构造正则算子，从而提供了建立正则化方法的理论依据。

If singular value curve is convex in the coordinates 'k' of maximum peak of curvature spectrum, then the number of effective singular values is k; if singular value curve is concave in the coordinates 'k', then the number of effective singular values is k-1, and this rule is tested by the signal processing examples.

如果奇异值曲线在曲率谱最大峰值的位置坐标k处是凸出的，则有效奇异值的个数为k；如果奇异值曲线在k处是凹进的，则有效奇异值的个数为k-1，通过信号处理实例证实了这种结论。

Studies show that multifractal spectra of log data are rarely symmetrical, but have steepened slopes on their left branches where the singularity strengths are higher. This indicates more rapid variations in fractal dimensions for highly singular data points in the data series.

研究表明实测的测井数据的多重分形谱很少是对称的，一般是左侧奇异值小的分支比右侧奇异值大的分支的斜率要大，显示了较奇异的点的分数维随着奇异值的变化而有较快的变化。

Based on this result,the intrinsic reasons that singular value vector-based recognition methods have the low recognition accauracy are follows: singular value vectors of arbitrary two face images have not the equivalent basis space in general;there is no one-to-one correspondence between singular value vector and face image;singular value vectors are not separated.

进一步研究发现，导致基于奇异值向量人脸识别算法识别率低的根本原因是：不同人脸图像对应的奇异值向量所在的基空间不一致、奇异值向量与人脸图像之间并不存在一一对应关系、奇异值向量具有不可分割性。

This chapter clarifies the nested relationship between the matrix family of unitary, orthogonal, Givens, Householder, permutation, and row or column symmetric matrices. A precise correspondence of the singular values and singular vectors between the unitary-symmetric matrix and its mother matrix is derived and proved (hence a fast algorithm of singular value decomposition for unitary-symmetric matrix is straightforwardly obtained), and the corresponding perturbation bound is provided.

该章揭示了酉对称矩阵、正交对称矩阵、 Givens 对称矩阵、 Householder 对称矩阵、置换对称矩阵和行对称矩阵之间的逐级包含关系；推导并证明了，酉对称矩阵的奇异值和奇异向量与母矩阵的奇异值和奇异向量之间的定量关系，据此可得酉对称矩阵奇异值分解的快速算法；给出并证明了摄动矩阵的摄动界。

Seeing image as a matrix, the method applied singular value decomposition on image matrix to decompose image information to a series of sub-spaces correspond to singular value and singular value vector, and then by reconstruction of image matrix using effective singular value to remove noising.

从矩阵的角度出发，通过对图像矩阵进行奇异值分解，将包含图像信息的矩阵分解到一系列奇异值和奇异值矢量对应的子空间中，然后通过有效奇异值重构图像矩阵达到去噪目的。

SVD can reflect the algebra character of the image effectively, and then through SVD operation on vehicle image matrix which includes singular value dimensionality reduction and singular value vector compositor, the feature subspace for recognition is established.

奇异值分解是基于代数特征的特征提取，经过对车辆图像矩阵的奇异值分解，再经过奇异值降维压缩和奇异值矢量排序，最后建立了用于识别的特征子空间。

The singular values of the project can be used as the character vector. The singular values of the scaling invariant can be obtained by the statistical characteristics of Radon transform. Since the singular values of the matrix are uncorrelated with the position of the column or the row of the matrix. In this way, the character vector of singular values with shift, scaling and rotational invariant is arrived at by this algorithm.

针对各颜色分量，利用Radon变换的奇异值的统计特性提取了具有尺度不变性的奇异值，由于矩阵的奇异值分解具有旋转不变性，因此该奇异值为平移、尺度和旋转不变的特征向量。

The maximum peak coordinates in curvature spectrum, which indicates the maximum turning point position of singular value, is used to determine the number of effective singular values.

进而提出了奇异值曲率谱的概念，利用它来描述含噪信号奇异值曲线上的转折点情况，并提出根据曲率谱最大峰值位置即奇异值最大转折点来确定有效奇异值个数。

与奇异值相关的网络解释 [注：此内容来源于网络，仅供参考]

nonsingular transformation：非奇异值转换

非奇异值 nonsingular | 非奇异值转换 nonsingular transformation | 无分选石环 nonsorted circle

singular values of a matrix：矩阵奇异值,矩阵奇异值

singular value decomposition SVD 奇异值分解 | singular values of a matrix 矩阵奇异值,矩阵奇异值 | singular verb 单动词

singular value decomposition of image matrix：影像矩阵奇异值分解

奇异集 singular set | 影像矩阵奇异值分解 singular value decomposition of image matrix | 单一值分解 singular value decomposition,SVD

singular value decomposition of image matrix：影像矩阵的奇异值分解

singular value decomposition 特異値分解 | singular value decomposition of image matrix 影像矩阵的奇异值分解 | singular value decomposition SVD 奇异值分解

singular value：奇异值

在把原图分成许多区块以后,将所有区块进行SVD, 再更改奇异值(Singular Value)以植入浮水印. 藉由计算变异系数及更改奇异值的方式,本技术能够同时兼顾数位浮水印之强韧性及不可察觉性. 不同於其他通常需要大量资讯才可萃取出数位浮水印之技术,

singular value：奇异值; 奇值

singular transformation 奇变换,奇异变换 | singular value 奇异值,奇值 | singular value decomposition 特異値分解

singular value decomposition：奇异值分解

最近,基于奇异值分解(singular value decomposition)的潜在语义标引(latent semantic indexing)已经应用于基因检索上. 然而,用于降低秩矩阵的因子K的取值仍然是一个悬而未解的问题. 结果:本文介绍了一种将基因关系的先验知识加入到LSI/SVD中来确定因子数的方法.

approximate singular value：近似奇异值

奇异值问题:singular value problem | 近似奇异值:approximate singular value | 最小奇异值:the smallest singular value

Structured Singular Value：结构奇异值

最小奇异值:the smallest singular value | 结构奇异值:Structured Singular Value | 奇异值阈值:Threshold of singular value

singular value problem：奇异值问题

截断奇异值法:truncated singular value method | 奇异值问题:singular value problem | 近似奇异值:approximate singular value