1) Discriminant Vector
鉴别矢量
1.
Improvement And Comparison Of Discriminant Vector Methods;
鉴别矢量集方法的改进与比较
2) discriminant vectors
鉴别矢量集
1.
Face recognition based on discriminant vectors derived from row vectors of matrix;
基于矩阵行矢量鉴别矢量集的人脸识别
3) discriminant vector angle
鉴别矢量角
1.
Face recognition based on discriminant vector angle embedding;
基于鉴别矢量角嵌入的人脸识别
4) optimal discriminant vectors
最优鉴别矢量集
1.
An improved kernel direct discriminant analysis(IKDDA) was proposed to compute the optimal discriminant vectors for the kernel-based Fisher discriminant analysis in singular cases.
针对奇异情况下核Fisher鉴别分析中非线性最优鉴别矢量集的求解问题,提出了改进的核直接描述分析(IKDDA)。
2.
The useful discriminant information in the null space of the kernel within—class scatter matrix and in the space of the kernel within—class scatter matrix was analyzed based on the kernel Fisher criterion,and an optimal discriminant vectors was acquired based on the idea of isomorphic mapping for the discriminant feature extraction of HRRP.
通过分析核Fisher准则函数下核类内散布矩阵的零空间信息与非零空间信息对识别的贡献,基于同构映射思想,求解出一组最优鉴别矢量集,用于提取距离像的鉴别特征。
3.
Then the problem of finding the optimal discriminant vectors subjected to such constraints is solved using the property that there exist a set of conjugate ort.
然后利用广义特征方程存在共轭正交的特征向量这一结论 ,巧妙地解决了该共轭正交条件下最优鉴别矢量集的求解问题 。
5) optimal discriminant vectors
最佳鉴别矢量
1.
Taking the AR model parameters as initial features, under the condition of the value of Fisher s discriminant function equaling to max, a set of optimal discriminant vectors is worked out.
针对复杂模式识别中的特征提取与选择问题,结合时间序列的参数模型和Fisher判别准则,提出了利用AR模型来拟合模式样本的时间序列,将模型参数作为原始特征矢量,然后在Fish-er鉴别准则函数取极大值的条件下,求得一组最佳鉴别矢量,最后再将高维原始特征矢量投影到这组矢量空间上来构成低维特征矢量的有效特征提取方法。
2.
The key of the method is how to calculate the optimal discriminant vectors.
Fisher最佳鉴别准则是高维模式分析中的有效方法 ,其关键是求解最佳鉴别矢量。
3.
Based on the maximum margin criterion(MMC),a new algorithm of orthogonal optimal discriminant vectors and a new algorithm of statistically uncorrelated optimal discriminant vectors for feature extraction were proposed.
基于最大间距准则(Maximum Margin Criterion,MMC)下,提出一组具有标准正交性的最佳鉴别矢量的计算方法和一组具有统计不相关性的最佳鉴别矢量的计算方法。
6) Optimal discriminant vector
最优鉴别矢量
补充资料：伯格斯矢量
分子式：
CAS号：
性质：是位错尺寸的量度。当位错在晶体内滑动时，原子沿着某一特定的方向相对于其邻近原子切变了某一特定的距离，表示这种原子位移的矢量定义为位错的伯格斯矢量。对螺型位错，位错线平行于伯格斯矢量；对刃型位错，位错线垂直于伯格斯矢量；对于混合型位错，位错线斜交于伯格斯矢量。
CAS号：
性质：是位错尺寸的量度。当位错在晶体内滑动时，原子沿着某一特定的方向相对于其邻近原子切变了某一特定的距离，表示这种原子位移的矢量定义为位错的伯格斯矢量。对螺型位错，位错线平行于伯格斯矢量；对刃型位错，位错线垂直于伯格斯矢量；对于混合型位错，位错线斜交于伯格斯矢量。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条