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singular value decomposition中文是什么意思

  • 奇异值分解

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  • 例句与用法
  • A least squares solution via singular value decomposition is used to solve the matrix equation . computations with synthetic data , where the near field of several typical antenna configurations are got over various geometric surface , illustrate the accuracy of the method
    为了证明本方法的计算准确性,我们给出了几个不同辐射源在不同近场测量几何面下的近场和远场计算结果,与解析公式的计算结果相比较,一致性很好。
  • Standard face images are formed through the above - mentioned processing . during the feature extraction , for those standard face images , regarding the between - class scatter matrix as generating matrix , we extract the algebraic features of face images through k - l transform and singular value decomposition
    在人脸特征提取过程中,对经过预处理的标准人脸图像,以类间散布矩阵为产生矩阵,通过k - l变换降维并结合奇异值分解来提取人脸代数特征。
  • Based on the equilibrium equation , the states of self - stress and the modes of inextensional mechanisms are solved by the singular value decomposition method . and the equilibrium equation can be solved by the generalized inverse method . the force density method is proposed
    在建立空间杆件体系平衡方程的基础上,采用广义逆方法求解各种情况下的平衡方程,采用奇异值分解方法求解索杆的机构位移模态和自应力模态,并推导了力密度方法的基本公式。
  • Firstly , unlike the factorization - based methods that minimize the svd ( singular value decomposition ) re - projection error , the method uses the minimization of mean 2d re - projection error of projective points as a criterion , therefore it has a clearer physical meaning and enhances the accuracy of projective reconstruction results
    该方法以全局性极小化射影三维空间点的二维反投影误差平方和为准则,相对于缩小svd反投影误差的方法,具有更为明确合理的物理意义。
  • Lingo is based on lsa theory and gets latent concept used for clustering description from search summarization . it constructs the related matrix of term , phrase and summarization , and makes singular value decomposition and similarity computation . this thesis implements web page on - line clustering
    该聚类算法基于潜在语义分析理论,利用检索结果的摘要进行潜在概念的获取并作为聚类描述,通过词、短语、摘要构建相关矩阵,进行奇异值分解和相似度计算,实现了网页在线聚类。
  • Some linear approaches reported recently without postprocessing to fir system identification are discussed . this paper improves the question of the promulgation of error due to estimating middle parameter frequently in other related methods , and presents a direct algorithm of estimating parameter without estimating middle coefficient . through proper mathematic means , for example , singular value decomposition ( svd ) or total - least squares solution ( tls ) , this algorithm smoothes the noise and improves effectively the estimation performance
    和2阶统计量相比,高阶统计量不仅能够有效抑制高斯有色噪声的影响,而且能够揭示随机过程的相位特性,因此,高阶统计量是解决非高斯、非最小相位、非因果系统和有色高斯噪声环境的系统辨识和处理问题的重要分析工具。
  • Considering the long - term characteristics of fault detect or system monitoring , the paper propose the extended kalman filter based on singular value decomposition to improve the numerical stability , and it accomplish fault detect or system monitoring based on the method . 5 . based on the conventional fourier transform and windowed fourier transform , the dissertation analysis the spectral of the inverter output signal
    由于调速系统的故障检测或状态监控具有长时间性的特点,为提高参数估计的数值稳定性,引入了奇异值分解理论,提出了基于奇异值分解的扩展卡尔曼滤波方法,并基于此方法实现了电动机变频调速系统的故障检测。
  • A new method was given out in this paper , which is based on the singular value decomposition of the balance matrix of truss , followed by the method of optimization under linear constrained condition . an analysis program for this method was developed . the rightness o f t his method w as proven by the analysis and verify of engineering example
    本文从桁架理论的奇异值分解出发,结合有约束线性优化方法,提出了解决这一问题的另一途径,编制了相应的分析程序,经过算例分析与验证,证明了该方法的正确性。
  • The current trends of this field is to acquire the current density of dipole distribution rather than a few dipoles . based upon that , a new model was proposed - dipole layer localization method ( dllm ) : spherical dipole layer was used as source model , on which dipoles were distributed by equilateral triangles ; three concentric inhomogeneous sphere was used as head model , which contains scalp , skull and cortex with different conductance . the dipole distribution and scalp potential tomography were obtained with singular value decomposition ( svd )
    鉴于该领域的研究趋势已从求取少数偶极子过渡到偶极子分布密度的获得,本文提出了新的模型? ?偶极面定位方法( dipolelayerlocalizationmethod , dllm ) :以等边三角形均匀分布的偶极子构成的偶极面(球面)作为源模型;包括头皮、颅骨和皮层的三层同心介质球作为头颅模型,运用奇异值分解来求解逆问题,从而获得偶极子分布和头皮电位分布,实现三维成像。
  • Singular value decomposition ( svd ) analysis shows significant correlation exists between pacific ssta pattern similar to peak - mature phase of el nino event and remote response pattern of pna and wp in 500 hpa geopotential height , which is further confirmed by svd analysis between ssta and 850 hpa wind fields
    太平洋ssta与大气500hpa高度场异常的svd分析表明,太平洋海温状况与pna以及wp遥相关型存在密切的相关,而850hpa风场与太平洋ssta的svd分析进一步反映了海温异常与大气遥相关间的联系。
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  • 百科解释
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix, with many useful applications in signal processing and statistics.
详细百科解释
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