- 更多网络例句与向量空间基底相关的网络例句 [注：此内容来源于网络，仅供参考]
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Every basis of a linear space contains the same number of vectors.
一线性空间的每一基底包含同样数目的向量。
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The components and the abstract structure, including the basis and dimension, of the vector space are followed.
然后说明抽象的向量空间的基本架构，包括基底与维度等。
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Play: 72. Arbitrary vector space of three linear independent base of representation.
播放：72。空间中任意向量的三线性独立基底的表示方法。
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It relies on the facts that the rows composed of all the image points span the same linear subspace as the rows composed of the 3D space points and that the basis of the subspace can consist of the two rows composed of the first image points and a row vector which is orthogonal to the former.
所有图像序列构成的行向量与3维空间点构成的行向量所生成的子空间是同一线性子空间，而且由第1幅图像点构成的2个行向量外加1个行向量就可以组成该子空间的一个基底。
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An iterative factorization method based on linear subspace for projective reconstruction is presented in the paper. It relies on the facts that the rows in the matrix including all the image points span the same linear subspace as the rows in the matrix including space points and the fact that any basis of the subspace can be regarded as projective reconstruction. The projective reconstruction and the depth factors are obtained based on linear iteration.
摘要该文提出了一种基于子空间线性迭代的射影重建方法，该方法利用所有的图像序列构成的行向量生成的线性子空间之和与射影重建结构点构成的行向量生成的子空间是同一线性子空间及在该子空间中任何一个基底都可以作为射影重建的特性，线性迭代地求取射影重建及图像深度因子。
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The method relies on the facts that the row vectors composed of all the image points span, the same linear subspace as the row vectors composed of 3D space points span and that a basis of the subspace can consist of two row vectors composed of all the image points and one row vector in 3D space that is orthogonal to the former. The row vector can be determined, and the 3D reconstruction is accomplished. The novelty lies in the fact that the method can treat all the image points uniformly.
利用所有图像序列构成的行向量生成的子空间之和与三维空间点构成的行向量生成的子空间是同一线性子空间、同时由所有图像点构成的2个行向量外加一个行向量就可以组成该子空间的一个基底的特性，线性地求取子空间中的行向量，最后完成三维重建。
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Instead of statistical description, a feature subspace with the base of some significant eigen vector extracted from covariance matrix is constructed to describe speech feature distribution of speaker. Distance metrics for measuring distance between input feature vector and subspace are also proposed for pattern matching.
说话人语音训练样本提取特征后在语音特征观察空间形成具有一定散度的分布，根据主元分析原理和分布散度提取主要散度本征向量作为基底构成说话人语音特征子空间，并通过测试语音特征矢量与子空间的距离测度进行模式匹配。
- 更多网络解释与向量空间基底相关的网络解释 [注：此内容来源于网络，仅供参考]
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basis of vector space：向量空间基底
power-on self-test 开电自检 | test board bay 测试台机架 | basis of vector space 向量空间基底
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feature extraction：特徵粹取
特徵粹取(feature extraction)是特徵选取(feature selection)的延伸,简单地说,我们希望将资料群由高维度的空间中投影到低维度的空间,因此,我们必须找出一组基底向量(base)来进行线性座标转换,使得转换后的座标,能够符合某一些特性.