Description: PCA（主成分分析）算法被广泛应用于工程和科学研究中，本报告主要从PCA的基本结构和基本原理对其进行研究，常规的PCA算法主要采用线性算法，通过研究论证发现线性的PCA算法存在着许多不足，比如线性PCA算法不能从线性组合中把独立信号成分分离出来，主分量只由数据的二阶统计量—自相关阵确定，这种二阶统计量只能描述平稳的高斯分布等，因此必须对其进行改进，经改进后的PCA算法有非线性PCA算法、鲁棒算法等。我们通过PCA算法在直线（平面）中拟和的例子说明了PCA在工程中的应用。本例子采用的是成分分析中的次成分（方差最小的成分），通过对结果的分析，我们可以看出，利用PCA算法可以得到较好的拟和结果。-PCA (Principal Component Analysis) algorithm has been widely used in engineering and science research, This report mainly from the PCA and the basic structure of the basic tenets of its research, Conventional PCA algorithm used mainly linear algorithm, found through research and demonstration linear PCA algorithm, there are many inadequate, For example, not linear PCA algorithm from the linear combination of the independent signal components separated, PCA data only from the second-order statistics-auto-correlation matrix to determine, Such second-order statistics can only describe a smooth Gaussian distribution, it is necessary to improve it. After the improvement of the PCA algorithm is nonlinear PCA algorithm, robust algorithm. PCA algorithm we passed the line (plane), and to be example Platform: |
Size: 454700 |
Author:东方云 |
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Description: PCA（主成分分析）算法被广泛应用于工程和科学研究中，本报告主要从PCA的基本结构和基本原理对其进行研究，常规的PCA算法主要采用线性算法，通过研究论证发现线性的PCA算法存在着许多不足，比如线性PCA算法不能从线性组合中把独立信号成分分离出来，主分量只由数据的二阶统计量—自相关阵确定，这种二阶统计量只能描述平稳的高斯分布等，因此必须对其进行改进，经改进后的PCA算法有非线性PCA算法、鲁棒算法等。我们通过PCA算法在直线（平面）中拟和的例子说明了PCA在工程中的应用。本例子采用的是成分分析中的次成分（方差最小的成分），通过对结果的分析，我们可以看出，利用PCA算法可以得到较好的拟和结果。-PCA (Principal Component Analysis) algorithm has been widely used in engineering and science research, This report mainly from the PCA and the basic structure of the basic tenets of its research, Conventional PCA algorithm used mainly linear algorithm, found through research and demonstration linear PCA algorithm, there are many inadequate, For example, not linear PCA algorithm from the linear combination of the independent signal components separated, PCA data only from the second-order statistics-auto-correlation matrix to determine, Such second-order statistics can only describe a smooth Gaussian distribution, it is necessary to improve it. After the improvement of the PCA algorithm is nonlinear PCA algorithm, robust algorithm. PCA algorithm we passed the line (plane), and to be example Platform: |
Size: 454656 |
Author:东方云 |
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Description: 对所采集到的非线性信号进行数据预处理,消除趋势项,球得其关联维数-Of the collected data pre-processing of nonlinear signals, eliminating the trend, the ball get the correlation dimension Platform: |
Size: 1024 |
Author:yutou |
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Description: 研究典型相关分析的各种线性算法和非线性算法，并通过实验数据的比较说明了它们各自的特点-Canonical Correlation Analysis Study of the various linear and nonlinear algorithms algorithms, and through comparison of experimental data shows the characteristics of their respective Platform: |
Size: 1555456 |
Author:黄清平 |
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Description: GCV Generalized cross-validation.广义交叉校验,用做非线性时间序列的计算，非常有用，找了好久才找到的。不要错过机会哦-GCV Generalized cross-validation. Generalized cross-validation, using nonlinear time series to do the calculation, is very useful to find for a long time to find the. Oh, do not miss the opportunity to Platform: |
Size: 2048 |
Author:zhxj |
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Description: 计算非线性信号与5阶gold序列互相关程度大小的程序，含5阶gold序列的生成。并分析自互相关性能-Calculation of nonlinear signal and the 5-order serial correlation degree of gold the size of the program, including five gold bands generated sequences. And analyzed from the correlation properties Platform: |
Size: 1024 |
Author:王任 |
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Description: 非线性信号处理之几何不变量。最大lyapunov和关联维数。-Nonlinear signal processing geometric invariant. Lyapunov and the largest correlation dimension. Platform: |
Size: 1568768 |
Author:xiaoxue |
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Description: Actual applications require specifi c methods to reduce the infl uence of the
correlation to distortions that appear when input images differ from their
reference model. When the distortion model can be described analytically
(such as in-plane rotation, scaling, etc.), specifi c methods give invariant
outputs to those particular distortions but reduces signifi cantly the fi eld of
practical applications. To overcome those limitations, we have fi rst proposed
the ASFS algorithm that allows to include a set of distorted images
in order to decrease the sensitivity of the correlation to nonanalytically
described distortions. Based on the ASFS algorithm, we have developed a
nonlinear two-step architecture Platform: |
Size: 7735296 |
Author:nahla |
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Description: MATLAB非线性混沌工具箱：时间延迟、嵌入维、最大李雅指数级关联维、熵等参数。有了自己就不用编程了！-The MATLAB nonlinear chaotic toolbox: the time delay, embedding dimension, maximum Josephine exponential correlation dimension, entropy and other parameters. With their own without programming! Platform: |
Size: 671744 |
Author:tianluo |
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Description: Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models. Platform: |
Size: 403456 |
Author:Shinva |
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Description: 本软件适合工程技术人员及学生进行数据分析。适用范围广、输入界面简单方便、功能模块实用强大、操作简便易懂。
本软件可进行二元线性与非线性相关分析；多元线性与非线性相关分析；多元线性的相关矩阵分析；数理统计与误差分析；计算行列式的值、求解多元方程组；学习与研究函数的图形及特性；计算常用函数等等。例如：可对化验分析成果进行回归及误差分析、对地质物化探数据进行相关性分析、对测量数据进行误差分析、对社会调查数据进行统计分析等等。 -The software for engineering and technical personnel and students for data analysis. Wide range of applications, the input interface is simple and convenient, functional modules and practical powerful, simple to understand. This software can be binary linear and non-linear correlation analysis multivariate linear and nonlinear correlation analysis multivariate linear correlation matrix analysis Mathematical Statistics and error analysis calculate the value of the determinant, solving multiple equations learning and research functions graphics, and features calculations commonly used functions and so on. For example: results of laboratory analysis can regression and error analysis, geophysical and geochemical data for geological correlation analysis, error analysis of the measurement data, the social survey data for statistical analysis and so on. Platform: |
Size: 7806976 |
Author:Gao |
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Description: 快速遗传剩余静校正方法(FGRS)
关键词： 互相关剩余静校正 遗传算法剩余静校正 快速遗传剩余静校正方法 大剩余静校正量
复杂地质地区（如复杂山地、山前带等），在野外静校正、折射或层析静校正等之后，仍可能存在大剩余静校正量，影响叠加效果。转换波剩余静校正量往往也较大，是转换波地震资料处理的难题之一。针对上述问题，研发了快速遗传剩余静校正方法，其特点是：
地表一致性
组合算法（互相关＋遗传算法）
非线性反演
快速高效
全局寻优
可解决大的纵波剩余静校正量问题(主要针对中高频量，可部分解决小的中低频量问题)
可部分解决转换波剩余静校正量问题
实际数据处理效果较好，对大剩校量的解决优于主流商业软件-fast genetic residual static correction method (FGRS)
Keywords : cross-correlation residual statics residual statics fast genetic algorithm genetic residual statics method large residual statics
Complex geological areas ( such as complex mountain , piedmont zone , etc. ) , in the field statics , refraction statics or chromatography , etc. After that, there may still be a large residual statics , the impact of overlay effect . Converted wave residual statics often larger problem is one of the converted wave seismic data processing . In response to these problems , the fast development of genetic residual static correction method , which is characterized by :
Surface consistency
Combination algorithm ( cross-correlation+ genetic algorithm )
Nonlinear inversion
Fast and efficient
Global optimization
Solve large longitudinal wave residual statics problem ( mainly for high frequency volume can partially solve the problem of small amount of low-frequenc Platform: |
Size: 1283072 |
Author: |
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Description: 对所采集到的非线性信号进行数据预处理,消除趋势项,球得其关联维数-Of the collected data pre-processing of nonlinear signals, eliminating the trend, the ball get the correlation dimension Platform: |
Size: 1024 |
Author:taway |
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Description: MIC最大信息数；用来表针变量的相关性大小（适用于线性和非线性情况）。MIC具有以下三条重要性质：1）如果变量x，y存在函数关系，则当样本增加时，MIC值趋于1；2）如果变量x，y可以有参数方程c(t)=[x(t),y(t)]所表达的曲线描述，则当样本增加时，MIC值必然趋于1；3）如果变量x,y相互独立，则当样本增加时，MIC值必然趋于0.-MIC maximum number of information correlation to the size of the hands of variables (for linear and nonlinear case). MIC has the following three important properties: 1) If the variable x, y presence function, then when the sample increases, MIC values towards 1 2) If the variable x, y can have a parametric equation c (t) = [x (t curve representation), y (t)] are expressed when the sample is increased, MIC values inevitably tends to 1 3) If the variable x, y independently of one another, then when the sample is increased, MIC values inevitably tends to zero. Platform: |
Size: 11076608 |
Author:zhangman |
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Description: 应用matlab，使实测速度数据转化为频域值，采用FFT和非线性最小二乘法进行模拟，在应用相关函数得到功率谱。-Application matlab, so actual speed data into the frequency domain values, simulated using FFT and nonlinear least squares method in the application to obtain the power spectrum correlation function. Platform: |
Size: 1024 |
Author:王剑 |
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Description: 利用非线性相关函数实现了一种多图像快速认证的算法~~利用图像分组与非相关峰的位置判断图像-Nonlinear correlation function implements a more image authentication algorithm quickly ~ ~ using image group and the correlation peak position to judgeNonlinear correlation function implements a more image authentication algorithm quickly ~ ~ using image group and the correlation peak position to judge Platform: |
Size: 1804288 |
Author:Xianye Li |
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Description: 到达过程是的泊松过程，这个有中文注释，看得明白，基于分段非线性权重值的Pso算法，最小均方误差（MMSE）的算法，用MATLAB实现的压缩传感，含噪脉冲信号进行相关检测。- Arrival process is a Poisson process, The Chinese have a comment, understand it, Based on piecewise nonlinear weight value Pso algorithm, Minimum mean square error (MMSE) algorithm, Using MATLAB compressed sensing, Noisy pulse correlation detection signal. Platform: |
Size: 4096 |
Author:sicrcq |
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Search - nonlinear correlation