1) normalized central moments
正则中心矩
2) first order central moment
修正一阶中心矩
1.
If the modified first order central moment BF <0, there is fault, and if BF >0 there is not fault.
检测到的母线电压进行S变换,提取S变换时频等值线和幅值包络向量,根据是否含高频分量和等值包络向量的修正一阶中心矩的正负,直观准确地实现类型识别,并对特征提取和识别算法进行研究。
3) regular matrix
正则矩阵
1.
Firstly the TPS is introduced into the theory of Semi-parametric regression,and then the regular matrix R is deduced.
提出了一种受多维变量影响的解决系统误差的半参数估计的薄板样条法,分析了其正则矩阵R,以某一重力异常数据处理算例验证了其正确性与可行性。
2.
Making use of Beasley s Lemma and permanent we obtain the row rank, column rank and Schein rank are identical for a regular matrix over a commutative semiring and the necessary and sufficient conditions for invertibility of matrices over an incline.
利用Beasley的引理以及不变式,获得了交换半环上正则矩阵的行秩、列秩与Schein秩三者相等,以及坡上矩阵可逆的充要条件。
4) positive semidefinite centro symmctric matrix
半正定的中心对称矩阵
5) regularizer
正则化矩阵
1.
One of the crucial steps is choosing an appropriate regularizer in processing GPS systematic errors based on the semi-parametric model.
基于半参数模型的GPS系统误差处理的关键之一是选择合适的正则化矩阵。
2.
Two new regularizers are employed to separate systematical errors in GPS baselines.
采用了两个新的正则化矩阵来分离高精度GPS基线向量处理中的系统误差,一是利用时间序列法选择的正则化矩阵;二是应用平稳随机过程的自协方差函数从双差观测值中提取的正则化矩阵。
3.
On the one hand,the ill condition of the normal equation was weakened by proper selection of a reasonable regularizer based on TIKHONOV regularization principle and much precision float ambiguities were obtained.
提出了只利用少数历元的GPS单频相位数据快速定位的新方法,主要从两方面考虑:一方面基于TIKHONOV正则化原理,通过构造合理正则化矩阵来减弱法方程的病态性,得到较准确的模糊度浮动解及其相应的均方误差阵;另一方面采用改进的白化滤波方法固定模糊度。
6) reinforced regular matrix
强正则矩阵
补充资料：矩则
1.规矩法则。
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