Description: A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archive. The C-code computes the DWT and maximal overlap DWT. MATLAB routines are then used to compute such quantities as the wavelet variance, covariance, correlation, cross-covariance and cross-correlation. Approximate confidence intervals are available for all quantities except the cross-covariance and cross-correlation.
A set of commands is provided. For a description of this example, please see http://www.eurandom.tue.nl/whitcher/software/. Platform: |
Size: 38711 |
Author:yupenghui |
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Description: A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archive. The C-code computes the DWT and maximal overlap DWT. MATLAB routines are then used to compute such quantities as the wavelet variance, covariance, correlation, cross-covariance and cross-correlation. Approximate confidence intervals are available for all quantities except the cross-covariance and cross-correlation.
A set of commands is provided. For a description of this example, please see http://www.eurandom.tue.nl/whitcher/software/. -A series of. C and. M files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary- everything is contained in this archive. The C-code computes the DWT and maximal overlap DWT. MATLAB routines are then used to compute such quantities as the wavelet variance, covariance, correlation, cross-covariance and cross-correlation. Approximate confidence intervals are available for all quantities except the cross-covariance and cross-correlation.A set of commands is provided . For a description of this example, please see http://www.eurandom.tue.nl/whitcher/software/. Platform: |
Size: 37888 |
Author:yupenghui |
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Description: 基于随机过程的莱斯表达式产生窄带随机过程：
2、掌握窄带随机过程的特性，包括均值（数学期望）、方差、相关函数及功率谱密度等。
-Rice random process based on the expression of narrow-band random process generated: 2, grasp the characteristics of narrow-band random process, including the mean (mathematical expectation), variance, correlation function and power spectral density and so on. Platform: |
Size: 45056 |
Author:kevin |
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Description: 针对传统图像相关匹配算法计算量较大的问题,研究图像库中相关图像搜索方法. 提出一种改进的相关
匹配算法,该方法通过对相关系数公式进行简化和迭代运算,减少了重复运算. 通过设定参考图像与目标图像的相
关系数阈值,只需计算方差相差较小的点的相关系数,提高了运算速度,计算时间减少到原来的14 ％ ,甚至更短.
在文件夹的图像搜索中实现了图像的快速匹配.-Traditional image correlation algorithm to match the volume of the larger issues, research image library, image search method. An improved matching algorithm, the method of correlation coefficient formula and iterative calculations can be simplified, reducing duplication of computing. by setting the reference image and target image of the correlation coefficient threshold, simply calculating the variance of the point difference between the smaller the correlation coefficient to improve the computing speed, computing time was reduced to the original 14, or less. in the folder Image Search achieving rapid image matching. Platform: |
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Author:李锋 |
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Description: 1．产生[0,1]均匀分布的白噪声序列
(1) 打印出前50个数 (2) 分布检验
(3) 均值检验 (4) 方差检验
(5) 计算相关函数 Bx(i),i=0,±1,±2,…, ±10
-1. Generated [0,1] uniformly distributed white noise sequence (1) print out the top 50 the number of (2) the distribution of test (3) the mean test (4) of variance test (5) calculating the correlation function Bx (i), i = 0 , ± 1, ± 2, ..., ± 10 Platform: |
Size: 1024 |
Author:yanxiaoying |
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Description: 产生 正态白噪声序列
(1) 打印出前50个数 (2) 分布检验
(3) 均值检验 (4) 方差检验
(5) 计算相关函数 Bx(i),i=0,±1,±2,…, ±10。
B(m)=1/1000
-Have a normal white noise sequence (1) print out the top 50 the number of (2) the distribution of test (3) the mean test (4) of variance test (5) calculating the correlation function Bx (i), i = 0, ± 1, ± 2 , ..., ± 10. B (m) = 1/1000 Platform: |
Size: 1024 |
Author:yanxiaoying |
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Description: 通过测量小波变换产生图像的熵、方差、最大值、最小值、平均值及各子图像内小波变换系数间的相关性来确定各子图像应采取的编码策略-Wavelet transform generated by measuring the image entropy, variance, maximum, minimum, average and sub-image with the wavelet transform coefficients of correlation between each sub-image to determine the encoding strategy should be taken Platform: |
Size: 135168 |
Author:gyq |
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Description: 分块有损压缩图像忽略了块间相关性，重构时会产生块效应，该文提出一种空域自适应去块效应算法。对块边缘采用方向自适应
有理滤波，以弱化块效应。根据块的内部活动性将图像块分成平坦块和纹理块2 类，利用基于方差的空域检测方法检测出平坦块，并对平
坦块进行邻块边缘自适应平滑。实验结果表明，该算法有效去除了块效应，一定程度上提高了信噪比，算法简单且鲁棒性较好。-Block lossy compression image ignores the inter-block correlation, Reconstruction would have a blocking effect, the paper presents a airspace Adaptive Deblocking Algorithm. To block the edge of rational use of the direction of adaptive filtering, in order to weaken the block effect. According to block the internal activity of the image block is divided into a flat block and texture block 2 categories, the use of airspace based on the variance detection methods to detect the flat block, and a flat block adjacent block edge adaptive smoothing. Experimental results show that the algorithm effectively blocking go except, to some extent, improve the signal to noise ratio, the algorithm is simple and better robustness. Platform: |
Size: 147456 |
Author:子登 |
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Description: 使用INTEL矢量统计类库的程序,包括以下功能:
Raw and central moments up to 4th order
Kurtosis and Skewness
Variation Coefficient
Quantiles and Order Statistics
Minimum and Maximum
Variance-Covariance/Correlation matrix
Pooled/Group Variance-Covariance/Correlation Matrix and Mean
Partial Variance-Covariance/Correlation matrix
Robust Estimators for Variance-Covariance Matrix and Mean in presence of outliers-INTEL vector statistical library use procedures, including the following features: Raw and central moments up to 4th order Kurtosis and Skewness Variation Coefficient Quantiles and Order Statistics Minimum and Maximum Variance-Covariance/Correlation matrix Pooled/Group Variance-Covariance/Correlation Matrix and Mean Partial Variance-Covariance/Correlation matrix Robust Estimators for Variance-Covariance Matrix and Mean in presence of outliers Platform: |
Size: 114688 |
Author:mktresearch |
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Description: 典型时间序列模型分析
设有ARMA(2,2)模型，
X（n）+0.3X(n-1)-0.2X(n-2)=W(n)+0.5W（n-1）-0.2W(n-2)
W(n)是零均值正态白噪声，方差为4
（1）用MATLAB模型产生X（n）的500观测点的样本函数，并会出波形；
（2）用你产生的500个观测点估计X（n）的均值和方差；
（3）画出理论的功率谱
（4）估计X（n）的相关函数和功率谱
-Analysis of typical time series model with ARMA (2,2) model, X (n)+0.3 X (n-1)-0.2X (n-2) = W (n)+0.5 W (n-1)-0.2 W (n-2) W (n) is zero mean normal white noise, variance of 4 (1) generated by MATLAB model X (n) of the 500 observation points, the sample function and the waveform (2) You generated an estimated 500 observation points X (n) the mean and variance (3) draw the theory of power spectrum (4) of the estimated X (n) of the correlation function and power spectrum Platform: |
Size: 3072 |
Author:qiuxue |
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Description: 了解随机信号自身的特性，包括均值（数学期望）、方差、相关函数、频谱及功率谱密度等。-Understanding of random signal their characteristics, including mean (mathematical expectation), variance, correlation function, spectrum and power spectral density. Platform: |
Size: 1024 |
Author:yaya |
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Description: 这是模式识别中最小错误率Bayes分类器设计方案。
自行完善了在不同先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。
全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。
调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。
调用最小错误率贝叶斯分类器决策子函数时，根据先验概率数组，通过比较概率大小判断一个体重身高二维向量代表的人是男是女。
主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小错误率贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到不同先验概率条件下错误率的统计。
-This is the minimum error rate pattern recognition Bayes classifier design.
Self- improvement prior probability in different conditions , male , female and total error rate error rate statistics , into which each array .
All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions .
Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector third step is to application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function .
Call the minimum error rate decision Functions Bayesian Platform: |
Size: 4096 |
Author:崔杉 |
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Description: 这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。
全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。
调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。
调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。
主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。
-This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array .
All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions .
Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function .
Bayesian classifier Platform: |
Size: 4096 |
Author:崔杉 |
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Description: 自己编的Allan方差计算函数，经过了反复测试。输入为陀螺频率数据和采样时间间隔。可以自定义只计算部分相关时间对应方差值。-Allan variance calculation function, after repeated tests. Input is the gyro frequency data and the sampling time interval. The part of the correlation time corresponding to the variance Can customize Platform: |
Size: 1024 |
Author:周春雷 |
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Description: 图像配准是多传感器图像融合研究中的一项关键技术。多传感器图像特别是波段相距较远的相
关性较小的图像，要实现图像配准存在很大的困难。对于能够用仿射变换模型来描述的图像，图像之间比较
明显的特征是各个物体之间的边缘．该文研究利用小波变换的方法提取图像的边缘，并对边缘图像作交互方
差分析，搜索出最佳交互方差的配准参数。通过对SPOT和TM图像的处理，达到了精度较高的配准效
果．-Image registration is a key technology in the study of the multi-sensor image fusion. Band distant correlation smaller image, to achieve image registration, there are great difficulties in multi-sensor image. For affine transformation model to describe the image, the more obvious features in the image between the edge between the respective objects. This paper studies the use of wavelet transform to extract image edge, and the edge of the image for interactive analysis of variance, and search out the best interactive variance of the registration parameters. SPOT and TM image processing, to achieve a higher accuracy with prospective effect. Platform: |
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Author:liu |
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Description: 电网内的多个风电场风速往往因为其地理位置的远近而有着不同程度的相关性，采用Ｎａｔａｆ
逆变换技术即可建立不同风电场之间具有相关性的风速分布样本空间，进而得到具有相关性的风
电场出力。在仿真过程中考虑风速的不确定性，将每个风电场出力视为一个负的满足威布尔随机
分布的负荷，根据历史数据，用方差—协方差矩阵描述不同风电场相关系数，建立最优潮流模型。
最后，在风电接入改进ＩＥＥＥ ３０及ＩＥＥＥ １１８节点系统中应用蒙特卡洛仿真计算，定量研究随着风
电场之间相关性的增强，最优潮流结果各项指标的波动情况。-Multiple wind speed within the grid often because of their geographical proximity and have different degrees of relevance, Nataf inverse transform using technology to build wind speed distribution between the sample space with different wind farms correlation, and then get relevant The wind farm output. Consider wind uncertainty in the simulation process, the output of each wind farm to meet the load as a negative Weibull random distribution, based on historical data, variance- covariance matrix of correlation coefficients describing different wind farms, the establishment of optimal fashion models. Finally, to improve access to wind power IEEE 30 and IEEE 118-node system Monte Carlo simulation, quantitative research with enhanced correlation between wind farms, OPF result of fluctuations in the indicators. Platform: |
Size: 510976 |
Author:mzx |
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Description: 假设用图示所示的两个正交信号经由一个AWGN信道传输二进制信息，在持续期Tb的每个比特区间接收到的信号以10/Tb速率采样，即每个比特区间内10个样本，幅度为A。噪声是均值为零，方差为 的高斯过程。
写MATLAB程序，在方差为0,0.1,1.0和2.0时，完成接收信号和两种发射信号的每一种的离散时间相关，画出在时刻k=1,2,…,10相关器的输出。-Assuming an AWGN channel transmission via binary information in two orthogonal signals icon shown in the ratio of each signal received indirect SAR duration Tb to 10/Tb sampling rate, that is, within the range 10 samples per bit, amplitude A. Noise is zero mean and variance of the Gaussian process.
Write a MATLAB program, the variance is 0,0.1,1.0 and 2.0, to complete each of the two discrete-time signals and transmit the received signal correlation shown in the time k = 1,2, ..., 10 output of the correlator . Platform: |
Size: 2048 |
Author:卢昳丽 |
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Description: （1）产生N（0,1）正态分布的随机过程；
（2）产生正态分布随机过程外的任意一种随机过程；
（3）对随机过程的性能进行评估，包括概率密度函数、分布函数、均值、方差和相关函数。((1) The stochastic process of generating N(0,1) normal distribution;
(2) generating any random process outside the normal distribution random process;
(3) evaluate the performance of random process, including probability density function, distribution function, mean value, variance and correlation function.) Platform: |
Size: 4233216 |
Author:273089134 |
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Search - variance of correlation