2) weight law of variance
均方差权重法
3) mean square error
均方误差
1.
Firstly,screen the descriptors using support vector machine regression(SVR) by leave-one-out method based on the minimum mean square error(MSE),get the optimal kernel and the corresponding retained descriptors.
首先以均方误差(MSE)最小为原则,以留一法通过多轮末尾淘汰实施分子结构描述符的非线性SVR汰选并给出最优核函数和相应保留描述符;其次基于待测样本与训练样本保留描述符向量的欧氏距离,以不同k-近邻群子模型双重留一法预测值反映样本集的异质性;然后基于MSE最小,以留一法通过多轮末尾淘汰实施近邻群子模型的非线性SVR汰选并给出最优核函数和相应保留子模型;最后基于保留子模型以双重留一法实施组合预测。
2.
For the generalized linear model with aggregated data:Y=Xβ+u,Eu=0,Var(u)=σ2∑,this paper is built two kinds of biased estimators: ridge estimator β(k)and improved ridge estimator β(k)which are discussed some superiority to the estimators in the sense of mean square error.
在均方误差意义下,研究了它们的优良性,并将岭估计与改进岭估计进行了比较,推广了有关文献中的结果。
3.
As to seemingly unrelated regression system,a new biased contracting estimator of the parameters is put forward,which is the combination of generalized ridge covariance-improved estimator and Stein estimator,and the good features of this estimator in mean square error is discussed.
对于一类相依回归系统,结合广义岭型协方差改进估计与Ste in估计,提出了一种新的有偏压缩估计,,并讨论了该估计在均方误差下的优良性质。
4) mean square of error
误差均方
5) MSE
均方误差
1.
A Motion Estimation Algorithm Based on the Quantized DCT Coefficients MSE Criterion;
基于量化系数均方误差准则的运动估计算法
2.
For a class of seemingly unrelated regression system consisting of two equations,an improved estimation of principal components is proposed and the optimal properties are discussed in the sense of mean squared error(MSE).
针对两个相依方程组成的一类回归模型,提出回归系数的一种组合主成分改进估计方法,在均方误差意义下讨论了这种估计量的优良性质,研究了此估计与主成份改进估计的关系。
3.
Under the MSE criterion,some properties of the improved c-k estimators are given.
针对设计矩阵Xi呈病态时的半相依线性回归系统,提出了系统参数iβ的一种c-k型改进估计,并证明了这种估计在均方误差意义下的若干优良性质。
6) mean square error(MSE)
均方误差
1.
Computer simulations show that the proposed algorithms lead to faster convergence rates and lower steady-state Mean Square Error(MSE) after convergence compared with the concurrent CMA and SDD algorithm.
从仿真结果看,两种新算法的收敛性能和稳态均方误差较CMA+SDD有了进一步提高,其中,MMA+SDD收敛性能最佳,SMMA+SDD的计算复杂度最低。
2.
A fast encoding algorithm based on the Mean Square Error(MSE) distortion for vector quantization is introduced.
研究了一种基于均方误差(MSE)测度的矢量量化快速编码算法。
3.
A fast encoding algorithm based on the mean square error(MSE) distance for vector quantization is introduced.
研究了一种基于均方误差(MSE)测度的矢量量化快速编码算法,算法利用小波变换的特点合理地构造矢量。
补充资料：因侵害姓名权、肖像权、名誉权、荣誉权产生的索赔权
因侵害姓名权、肖像权、名誉权、荣誉权产生的索赔权：公民、法人的姓名权、名称权，名誉权、荣誉权、受到侵害的有权要求停止侵害，恢复名誉，消除影响，赔礼道歉，并可以要求赔偿损失。
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