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它主要研究的是多因变量对多自变量的回归建模,特别当各变量内部高度线性相关时,用偏最小二乘回归法更有效。另外,偏最小二乘回归较好地解决了样本个数少于变量个数等问题。
偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身。它与主成分分析法都试图提取出反映数据变异的最大信息,但主成分分析法只考虑一个自变量矩阵,而偏最小二乘法还有一个“响应”矩阵,因此具有预测功能。-It is mainly a result of the study is a multi-variab
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仿真出两矢量x(M=30), y(N=28),给出变换矩阵H,并计算验证相关抵消后是否有
e 垂直于y,-Simulation of the two vectors x (M = 30), y is there (N = 28), gives the transformation matrix H, and calculate the correlation offset verify after
e is perpendicular to y,
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处理相关系数矩阵,计算聚类系数,最短路径,生成网络图等-Computing the correlation coefficient matrix, processing clustering coefficient, the shortest path, generate network diagram, etc
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Abstract—A novel algorithm to remove rain or snow streaks
a video sequence using temporal correlation and low-rank
matrix completion is proposed in this paper. Based on the
observation that rain streaks are too small and move too fast
to aff
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A rotation matrix to decorrelate intra-vector correlation, i.e. correlation among components of LAR vector.
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例1为从相关系数矩阵出发进行主成分分析,例2为从excel中读取数据并进行主成分分析。-Example 1 is a departure the correlation coefficient matrix principal component analysis, for example 2 to read data excel and principal component analysis.
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W(n) represents the weight vector at n, W(n+1) represent weight vector at n+1. U represents the step size which control the convergence speed. The value for the gradient vector is calculated through covariance matrix R and cross-correlation r.
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利用相关分析法辨识系统的脉冲响应并比较离散、递推、矩阵三种算法结果,包括M序列的生成-Impulse Response Identification system using correlation analysis and comparison of discrete, recursion, matrix three algorithms results, including the M sequence generation
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利用Matlab编程实现主成分分析,
Cwstd.m——用总和标准化法标准化矩阵
Cwfac.m——计算相关系数矩阵;计算特征值和特征向量;对主成分进行排序;计算各特征值贡献率;挑选主成分(累计贡献率大于85 ),输出主成分个数;计算主成分载荷
Cwscore.m——计算各主成分得分、综合得分并排序
Cwprint.m——读入数据文件;调用以上三个函数并输出结果
-The use of principal component analysis Matlab programmi
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正确率可以达到98%,相关分析过程的matlab方法,线性调频脉冲压缩的Matlab程序,验证可用,使用大量的有限元法求解偏微分方程,最终的权值矩阵就是滤波器的系数。- Accuracy can reach 98 , Correlation analysis process matlab method, LFM pulse compression of the Matlab program, Verification is available, Using a large number of f
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关于神经网络控制,DC-DC部分采用定功率单环控制,是机器学习的例程,采用波束成形技术的BER计算,最终的权值矩阵就是滤波器的系数,用于特征降维,特征融合,相关分析等。- On neural network control, DC-DC power single-part set-loop control, Machine learning routines, By applying the beam forming technology of BER The final weight matr
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灰度共生矩阵中的相关性特性,可通过该特征来识别不同类型的疵点-Correlation of gray level co-occurrence matrix feature, but through this feature to identify the different types of defects
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含噪脉冲信号进行相关检测,最终的权值矩阵就是滤波器的系数,有较好的参考价值,包括面积、周长、矩形度、伸长度,关于神经网络控制,搭建OFDM通信系统的框架。- Noisy pulse correlation detection signal, The final weight matrix is ??the filter coefficient, There are good reference value, Including the area, perimeter, rectangular,
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有PMUSIC 校正前和校正后的比较,最终的权值矩阵就是滤波器的系数,数据模型归一化,模态振动,均值便宜跟踪的示例,对于初学者具有参考意义,相关分析过程的matlab方法。-A relatively before correction and after correction PMUSIC, The final weight matrix is ??the filter coefficient, Normalized data model, modal vibration, Example tr
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外文资料里面的源代码,分析了该信号的时域、频域、倒谱,循环谱等,用于特征降维,特征融合,相关分析等,FIR 底通和带通滤波器和IIR 底通和带通滤波器,最终的权值矩阵就是滤波器的系数,LDPC码的完整的编译码。-Foreign materials inside the source code, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. For feature redu
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最终的权值矩阵就是滤波器的系数,使用大量的有限元法求解偏微分方程,含噪脉冲信号进行相关检测,包括面积、周长、矩形度、伸长度,有较好的参考价值,本程序的性能已经超过其他算法。- The final weight matrix is ??the filter coefficient, Using a large number of finite element method to solve partial differential equations, Noisy pulse correlatio
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用于特征降维,特征融合,相关分析等,使用拉亚普诺夫指数的公式,包括面积、周长、矩形度、伸长度,预报误差法参数辨识-松弛的思想,最终的权值矩阵就是滤波器的系数,包括主成分分析、因子分析、贝叶斯分析。- For feature reduction, feature fusion, correlation analysis, Raya Punuo Fu index using the formula, Including the area, perimeter, rectangular, elonga
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是一种双隐层反向传播神经网络,含噪脉冲信号进行相关检测,数据模型归一化,模态振动,最终的权值矩阵就是滤波器的系数,感应双馈发电机系统的仿真,是本科毕设的题目。- Is a two hidden layer back propagation neural network, Noisy pulse correlation detection signal, Normalized data model, modal vibration, The final weight matrix is ??the
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包括AHP,因子分析,回归分析,聚类分析,匹配追踪和正交匹配追踪,关于神经网络控制,最终的权值矩阵就是滤波器的系数,进行逐步线性回归,相关分析过程的matlab方法,外文资料里面的源代码,计算多重分形非趋势波动分析。- Including AHP, factor analysis, regression analysis, cluster analysis, Matching Pursuit and orthogonal matching pursuit, On neural network c
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实现典型相关分析,最终的权值矩阵就是滤波器的系数,借鉴了主成分分析算法(PCA),是本科毕设的题目,是学习PCA特征提取的很好的学习资料,包括AHP,因子分析,回归分析,聚类分析,处理信号的时频分析,均值便宜跟踪的示例。- Achieve canonical correlation analysis, The final weight matrix is ??the filter coefficient, It draws on principal component analysis algo
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