singular value decomposition
奇异值分解：一种矩阵分解的方法
常用释义
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基本释义
- 奇异值分解：一种矩阵分解的方法，将一个矩阵分解为三个矩阵的乘积，其中第二个矩阵是一个对角矩阵，其对角线上的元素是原始矩阵的奇异值。SVD在数据分析、信号处理、图像处理等领域有广泛应用。
例句
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1·Parallel Lanczos SVD (Singular Value Decomposition) solver.并行Lanczos SVD(奇异值分解)计算。
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2·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。
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3·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。
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4·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。
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5·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。
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6·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。
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7·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。
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8·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）。
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9·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。
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10·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。