orthonormalization meaning in Chinese
标准正交化
归一正交化
Examples
- By utilizing the main advantages of orthonormalization and power conservation from hilbert transformation , it is found that bit error rate is close to that of dcsk system , but transmission speed is one time higher than that of dcsk system , and the system ' s output variance is effectively reduced
基于qpsk的思想，引入qcsk调制方式，利用hilbert变换对正交且能量守恒的特性，有效减小了系统输出的方差，较dcsk系统，传输速率提高一倍，系统误比特率与dcsk系统相近。 - And forecast ability was compared between the models built by selecting factors as well as orthonormalization and the other models built by stepwise regression analysis directly . the comparative result was forecast ability of model by monadic linear regression analysis and nature orthonormalization function as well as stepwise regression was stronger than the models by direct stepwise regression analysis
比较得出:通过一元一次线性回归进行因子筛选，并对其进行正交化分析，再进行逐步回归建立的预报模型比直接利用逐步回归分析建立的模型的预报功能强的多。 - ( 3 ) the re - orthonormalization technique is used to solve the loss of orthonormality of basis vector during the classical gmres method solving large - scale three dimensional elasto - static be problems . based on the characteristic of fundamental solution and the coefficient matrix , several precondition methods are studied . by using the technique of re - orthonoramalization and precondition , the practical gmres method is developed based on the classical one
( 3 )采用重正交技术解决了经典gmres方法在求解大型三维弹性静力边界元问题过程中出现的基向量正交性丧失的问题；结合边界元基本解和系数矩阵的特点以及并行化的要求，研究了几种预条件技术；并以重正交技术和预条件技术实现了经典gmres的实用化。 - Aiming at the problem on taking no account of relation of forecast factors and instability of regression results caused by selected factors with no orthonormalization which would bring out error to computational results , monadic linear regression analysis and nature orthonormalization function as well as stepwise regression were integrated to establish forecast models of cold in nanjing and upper respiratory tract infection , cerebral hemorrhage as well as cerebral infarction in jinhua
过去在选择预报因子时没有考虑预报因子间的相关性，挑选的预报因子由于非正交使回归计算的结果不稳定，给计算带来一定的误差。针对这一问题，文章将一元线性回归分析、自然正交函数法( eof )和逐步回归方法结合起来，建立了南京感冒以及金华的上呼吸道感染、脑出血和脑梗塞的发病指数预报模型。并将模型结果与逐步回归法建立的模型进行比较。