Parallel Lanczos SVD (Singular Value Decomposition) solver.
并行LanczosSVD(奇异值分解)计算。
Singular value decomposition (SVD) has very important applications in image processing.
奇异值分解(SVD)在图像处理中具有极其重要的应用。
A least squares solution via singular value decomposition is used to solve the matrix equation.
本文使用奇异值分解法求解矩阵方程的最小二乘解。
Then, a method is presented based on the singular value decomposition to compute the minimal norm solution.
然后用奇异值分解给出了求解最小范数解的一种方法。
The problem of image matching and target tracking based on singular value decomposition (SVD) was discussed.
研究了基于奇异值分解的图像匹配和目标跟踪问题。
Using the singular value decomposition technique, the method for measuring the modal controllability is determined.
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。
A face identification method based on singular value decomposition (SVD) and data fusion is proposed in this paper.
提出了一种基于奇异值分解和数据融合的脸像鉴别方法。
The singular value decomposition least squares(SVDLS)method was improved for the various dynamic spectrum analysis.
本文改进了处理动态光谱的奇异值分解最小二乘法（SVDLS）。
The GGE data is then subjected to singular value decomposition and is approximated by the first two principal components.
对GGE 作单值分解，并以第一和第二主成分近似之。
The Singular Value Decomposition (SVD) method for the equilibrium matrix is developed and a physical explanation is given.
引入了平衡矩阵的奇异值分解（SVD）方法并解释了其力学含义。
An algorithm based on singular value decomposition (SVD) is proposed, which hides secret information in singular value vector.
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 improved SVD method was introduced by combining empirical orthogonal function (EOF) with singular value decomposition (SVD).
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。
This paper introduces a typical SNR estimation algorithm by the use of autocorrelation matrix singular value decomposition method.
主要介绍了一种典型的信噪比估计算法，并对信噪比的自相关矩阵奇异值分解估计法进行了研究。
A face recognition method based on the fusion of principal component analysis (PCA) and singular value decomposition (SVD) is presented.
提出了奇异值分解(SVD)和主分量分析(PCA)相结合的人脸识别算法。
By means of the damp least square method and singular value decomposition method, the misalignment of optical system could be calculated.
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 decomposing a matrix into one diagonalizable matrix and two orthogonal matrixes, singular value decomposition has very good properties.
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。
A general difficulty of using singular value decomposition (SVD) to split signal and noise subspaces is in the right choice of effective rank.
用奇异值分解界定信号和噪声子空间的困难之处，在于有效秩的确定。
In addition, a method based on singular value decomposition (SVD) was proceed to deal with the obtained result for dropping influence of noise.
为降低噪声的影响，采用一个基于奇异值分解(SVD)的方法对识别的结构进行处理。
A robust stability boundary of uncertain singular systems is proposed by utilizing singular value decomposition and the character of mode matrix.
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。
In order to solve these problems, a rank-truncated multi-station TDOA localization algorithm based on singular value decomposition was presented.
为了解决这些问题，提出了一种基于奇异值分解的秩截短多站时差定位算法。
Meanwhile to reduce the cost of memory space, this paper takes the Semi-Discrete Decomposition Method rather than the Singular Value Decomposition.
同时为了进一步降低存局部潜在语义分类的存储空间的开销，采用半离散分解方法替代奇异值分解方法。
Singular Value Decomposition (SVD) is a dimension reduction method, and Symbolic data Analysis (SDA) is a new analytical approach to processing mass data.
奇异值分解(SVD)是一种对数据进行降维处理的方法，符号数据分析(SDA)是一种处理海量数据的全新数据分析思路。
Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
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。
Digital image is transformed into singular value matrix that contains non-zero singular values by singular value decomposition (SVD), the image is compressed.
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。
Chaos map and singular value decomposition of matrix technology are introduced to improve the watermarking imperceptibility, security and robustness of watermark image.
利用混沌映射结合矩阵奇异分解，将水印信息分散在原始图像的不同位置，提高了水印的视觉效果，保证了水印的安全性。
The influence of noise on the computational precision of correlation dimension is discussed, and iterative singular value decomposition for reducing noise is introduced.
同时研究了噪声对关联维数计算结果的影响，并提出用采样迭代奇异值降噪算法对原始数据进行降噪处理。
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.
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.
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。
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