设有 k 个母体 G_1,G_2,…,G_k,F_i 为来自母体 G_i 的随机变量,P_i 为其概率密度,根据多元统计分析理论,可以求出母体内的协方差阵 W 和各母体间的协方差阵 B。当样本归属于不同的母体空间时,则会引起 W 和 B 的变化。若某一种归属能使...设有 k 个母体 G_1,G_2,…,G_k,F_i 为来自母体 G_i 的随机变量,P_i 为其概率密度,根据多元统计分析理论,可以求出母体内的协方差阵 W 和各母体间的协方差阵 B。当样本归属于不同的母体空间时,则会引起 W 和 B 的变化。若某一种归属能使 W^(-1)B 的度量达到极大,则认为这种归属达到最优,于是可用 W^(-1)B 的特征方程的根来度量 W^(-1)B。其所有根的和可以 tr(W^(-1)B)表示,tr(W^(-1)B)表示 W^(-1)B 的迹。利用最大迹的判别分析方法可以识别油气异常。文中给出判别准则及具体计算方法,并以一个试验区为例,选取构造、层厚度、层振幅、层频率和层速度等五个参数变量组成五元变量,进行方差分析、均值检验和评判,说明这种方法具有识别油气的能力。展开更多
A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the ...A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters.展开更多
基金Supported by the National Nature Science Foundation of China(No.61304205,61203273,61103086,41301037)the Open Funding Project of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.BUAA-VR-13KF-04)+1 种基金Jiangsu Ordinary University Science Research Project(No.13KJB120007)Innovation and Entrepreneurship Training Project of College Students(No.201410300153,201410300165)
文摘A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters.
