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• Parallel Lanczos SVD (Singular Value Decomposition) solver.

并行LanczosSVD(奇异分解)计算。

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• Singular value decomposition (SVD) has very important applications in image processing.

奇异分解(SVD)图像处理具有极其重要应用

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• A least squares solution via singular value decomposition is used to solve the matrix equation.

本文使用奇异分解法求解矩阵方程最小二乘

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• Then, a method is presented based on the singular value decomposition to compute the minimal norm solution.

然后奇异分解给出求解最小范数解的一种方法

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• The problem of image matching and target tracking based on singular value decomposition (SVD) was discussed.

研究基于奇异分解图像匹配目标跟踪问题

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• Using the singular value decomposition technique, the method for measuring the modal controllability is determined.

利用奇异分解技术确定了定量度量可控程度方法

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• A face identification method based on singular value decomposition (SVD) and data fusion is proposed in this paper.

提出一种基于奇异分解数据融合脸像鉴别方法

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• 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奇异分解最小二乘法SVDLS）。

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• The GGE data is then subjected to singular value decomposition and is approximated by the first two principal components.

GGE 作分解，并第一第二成分近似之

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• The Singular Value Decomposition (SVD) method for the equilibrium matrix is developed and a physical explanation is given.

引入了平衡矩阵奇异分解SVD方法解释了其力学含义。

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• An algorithm based on singular value decomposition (SVD) is proposed, which hides secret information in singular value vector.

给出一种基于矩阵奇异分解(SVD)和奇异值量化信息隐藏算法

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• An improved SVD method was introduced by combining empirical orthogonal function (EOF) with singular value decomposition (SVD).

奇异分解同自然正交分解相结合，提出一种改进的正交奇异分解方法

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• This paper introduces a typical SNR estimation algorithm by the use of autocorrelation matrix singular value decomposition method.

主要介绍一种典型估计算法，并信噪比的相关矩阵奇异分解估计进行了研究。

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• A face recognition method based on the fusion of principal component analysis (PCA) and singular value decomposition (SVD) is presented.

提出奇异分解(SVD)分量分析(PCA)相结合人脸识别算法。

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• By means of the damp least square method and singular value decomposition method, the misalignment of optical system could be calculated.

采用阻尼最小乘法奇异分解方法求解失调量

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• By decomposing a matrix into one diagonalizable matrix and two orthogonal matrixes, singular value decomposition has very good properties.

奇异分解是将矩阵分解对角矩阵两个正交矩阵，奇异值分解有着非常好的性质

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• A general difficulty of using singular value decomposition (SVD) to split signal and noise subspaces is in the right choice of effective rank.

奇异分解界定信号噪声空间困难之处，在于有效确定。

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• In addition, a method based on singular value decomposition (SVD) was proceed to deal with the obtained result for dropping influence of noise.

降低噪声影响，采用一个基于奇异分解(SVD)的方法对识别的结构进行处理

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• A robust stability boundary of uncertain singular systems is proposed by utilizing singular value decomposition and the character of mode matrix.

利用奇异分解方法矩阵性质给出了使不确定广义系统稳定一个鲁棒

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• 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分解的秩截短多站时差定位算法

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• 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存储空间开销采用离散分解方法替代奇异分解方法。

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• Singular Value Decomposition (SVD) is a dimension reduction method, and Symbolic data Analysis (SDA) is a new analytical approach to processing mass data.

奇异分解(SVD)种对数据进行处理方法符号数据分析(SDA)是一种处理海量数据的全新数据分析思路

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• Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.

传统特征提取方法主要有分量分析奇异分解投影追踪自组织映射

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• Digital image is transformed into singular value matrix that contains non-zero singular values by singular value decomposition (SVD), the image is compressed.

通过图像进行奇异分解，将一幅图像转换成只包含几个非零的奇异值矩阵，实现图像压缩。

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• 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，将水印信息分散原始图像不同位置，提高了水印的视觉效果，保证了水印的安全性。

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• The influence of noise on the computational precision of correlation dimension is discussed, and iterative singular value decomposition for reducing noise is introduced.

同时研究噪声关联维数计算结果影响提出用采样迭代奇异降噪算法原始数据进行降噪处理。

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• 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.

矩阵奇异分解广义讨论标准线性规划问题存在性唯一性问题。

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• 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.

矩阵奇异分解广义讨论标准线性规划问题存在性唯一性问题。

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