Description: 扩频通信中采用的线性调频算法用的复相关算法-spread spectrum communications using the linear FM algorithm of multiple correlation algorithm Platform: |
Size: 2625 |
Author:刘琴 |
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Description: 扩频通信中采用的线性调频算法用的复相关算法-spread spectrum communications using the linear FM algorithm of multiple correlation algorithm Platform: |
Size: 2048 |
Author:刘琴 |
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Description: 这是有关信道编码的matlab仿真程序，里面有很多子程序，很好用！-This is the channel coding of Matlab simulation program, there are many subroutine good use! Platform: |
Size: 26624 |
Author:刘娜 |
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Description: !逐步回归分析程序：
! M：输入变量，M=N+1，其中N为自变量的个数；M包括的因变量个数
! K：输入变量，观测点数；
! F1：引入因子时显著性的F-分布值；
! F2：剔除因子时显著性的F-分布值；
! XX：存放自变量和因变量的平均值；
! B：存放回归系数；
! V：存放偏回归平方和和残差平方和Q；
! S：存放回归系数的标准偏差和估计的标准偏差；
! C：存放复相关系数；
! F：存放F-检验值；-! Stepwise regression analysis procedure:! M: input variables, M = N+ 1, in which N is the number of independent variables M, including the number of the dependent variable! K: input variables, observation points ! F1: when to introduce a significant factor of the F-distribution value ! F2: remove significant factor when the F-distribution value ! XX: storage self-variables and the dependent variable on average ! B: regression coefficient storage ! V: store partial regression sum of squares and residual sum of squares Q ! S: storage of the standard deviation of regression coefficients and the estimated standard deviation ! C: storage of multiple correlation coefficient ! F: storing F-test value Platform: |
Size: 2048 |
Author:wang hanting |
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Description: 对随机变量以自变量的几组观测数据作多元线性回归（求得平均标准偏差，复相关系数和回归平方和）-Of random variables since the variables in several groups of observation data for multiple linear regression (obtained an average standard deviation, correlation coefficient and regression sum of squares) Platform: |
Size: 1024 |
Author:fuxiao |
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Description: Performs hierarchical clustering of data using specified method and
seraches for optimal cutoff empoying VIF criterion suggested in "Okada Y. et al - Detection of Cluster Boundary in Microarray Data by Reference to MIPS Functional Catalogue Database (2001)".
Namely, it searches cutoff where groups are independent. The techinque uses an econometric approach of verifying that variables in
multiple regression are linearly independent: if all the diagonal
elements of inverse correlation matrix of data are less than VIF-Performs hierarchical clustering of data using specified method and
seraches for optimal cutoff empoying VIF criterion suggested in "Okada Y. et al- Detection of Cluster Boundary in Microarray Data by Reference to MIPS Functional Catalogue Database (2001)".
Namely, it searches cutoff where groups are independent. The techinque uses an econometric approach of verifying that variables in
multiple regression are linearly independent: if all the diagonal
elements of inverse correlation matrix of data are less than VIF Platform: |
Size: 2048 |
Author:tra ba huy |
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Description: 本文给出了m序列多项相关性的概念，还研究了生成多项式计数的问题-In this paper, the concept of multiple correlation m series, also studied the problem of generation polynomial count Platform: |
Size: 133120 |
Author:刘志友 |
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Description: 对随机变量以自变量的几组观测数据作多元线性回回归（求的平均标准偏差，复相关系数与回归平方与）
-Argument of several sets of observational data for the multiple linear regression (ask the average standard deviation of the random variable, the multiple correlation coefficient and regression sum of squares) Platform: |
Size: 1024 |
Author:认可 |
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Description: 几个BOC 信号的分析例程，全球卫星导航系统将普遍使用BOC调制信号作为扩频测距信号，BOC信号号自相关函数呈现多个相关峰，传统扩频接收机所用的延迟锁定环（DLL）无法对该信号正确地进行码相位的
-Several BOC signal analysis routines, the global satellite navigation system will generally use the BOC modulation signal as a spread spectrum ranging signal, BOC signal autocorrelation function presents multiple correlation peaks, the traditional spread spectrum receiver with the delay locked loop (DLL ) can not be the signal code phase Platform: |
Size: 8192 |
Author:yanyantiao |
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Description: 偏最小二乘回归提供一种多对多线性回归建模的方法，特别当两组变量的个数很
多，且都存在多重相关性，而观测数据的数量（样本量）又较少时，用偏最小二乘回归
建立的模型具有传统的经典回归分析等方法所没有的优点。 -Partial least squares regression provides a many-to-many linear regression modeling methods, especially when the number of the two sets of variables, and the existence of multiple correlation, while the number of observations (sample size) and less created using partial least squares regression model with a traditional classical regression analysis method advantages. Platform: |
Size: 160768 |
Author:yangchenghu |
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Description: 逐步回归分析的fortran程序，（I为变换次数，矩阵为R(I)，Q为剩余平方和，SD为剩余标准差，F为显著性检验值，R为复相关系数，B为回归系数）-Stepwise regression analysis fortran program, (I was converted number matrix R (I), Q is the residual sum of squares, SD for the residual standard deviation, F is significant test value, R is the multiple correlation coefficient, B is the regression coefficient) Platform: |
Size: 2048 |
Author:ouc |
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Description: 地震信号处理，虚同相轴方法预测层间多次波，将数据分成上下两部分，利用相关和褶积的原理预测出层间多次波。预测信号和原始信号在相位和振幅上存在差异，用L1范数匹配法进行匹配，其中，提供了两种方法解病态方程，分别为高斯-赛德尔方法和正则化方法。-Seismic signal processing, predicte internal multiples by construct virtual events .The data is divided into two parts, using the principle of correlation and convolution to predicte multiples. There are differences between the prediction signal and the original signal on the phase and amplitude, so we use the L1 norm method to match the singal.We provide two methods for solving ill equation, respectively Gauss- Seidel method and regularization method. Platform: |
Size: 5120 |
Author:刘璐 |
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Description: 这是一种基于近红外光谱的非线性建模方法及系统，从各所述近红外光谱数据随机挑出一部分作为校正集，挑出一部分作为验证集；将所述校正集和所述验证集通过主成分分析得到光谱特征空间；在所述光谱特征空间中，通过马氏距离法选取所述校正集里与所述验证集的各个样本最近似的样本作为校正子集；从所述校正子集中提取主成分数，作为BP神经网络的输入层建立回归模型，不仅能解决各因素之间多重相关的问题，还避免了大量的噪声和一些无用的信息，降低了变量维数，在BP神经网络的非线性映射能力和适应学习能力的基础上，提高了模型的预测稳定性和精度。-This is a kind of nonlinear modeling method and system based on near infrared spectrum, described the near infrared spectrum data randomly selected part as calibrating, pick out the part as a validation set Will be described in the calibration set and described in the validation set is obtained by principal component analysis (spectral feature space It is spectral feature space, the selection method described by markov distance calibration set and validation set described in each sample with the sample as the calibration subsets Principal components extracted calibration described subset, as BP neural network input layer to establish a regression model, not only can solve the problem of multiple correlation among various factors, also avoid a lot of noise and some useless information, reducing the variable dimension, the nonlinear mapping ability of BP neural network and adaptive learning ability, on the basis of improve stability and accuracy of the prediction of the model. Platform: |
Size: 2048 |
Author:詹映 |
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Search - multiple correlation