当前位置:
首页
资源下载
![](/images/right.gif)
搜索资源 - feature extraction principal component analysis
搜索资源列表
-
0下载:
用于信号特征提取、信号消噪,借鉴了主成分分析算法(PCA),LCMV优化设计阵列处理信号。- For feature extraction, signal de-noising, It draws on principal component analysis algorithm (PCA), LCMV optimization design array signal processing.
-
-
0下载:
实现二维主成分分析功能,可应用于图像特征提取-Function of two-dimensional principal component analysis can be applied to image feature extraction
-
-
0下载:
用于信号特征提取、信号消噪,ICA(主分量分析)算法和程序,这是一个好用的频偏估计算法的matlab仿真程序。- For feature extraction, signal de-noising, ICA (Principal Component Analysis) algorithm and procedures, This is a useful frequency estimation algorithm matlab simulation program.
-
-
1下载:
:植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而,低维特征不能全面描述叶片信息,识别准确率低,本文提
出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理,获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征,对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征,对纹理图像提取分形维数,共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相
-
-
0下载:
在MATLAB中求图像纹理特征,是学习PCA特征提取的很好的学习资料,包括主成分分析、因子分析、贝叶斯分析。- In the MATLAB image texture feature, Is a good learning materials to learn PCA feature extraction, Including principal component analysis, factor analysis, Bayesian analysis.
-
-
0下载:
借鉴了主成分分析算法(PCA),利用matlab GUI实现的串口编程例子,是学习PCA特征提取的很好的学习资料。- It draws on principal component analysis algorithm (PCA), Use serial programming examples matlab GUI implementation, Is a good learning materials to learn PCA feature extraction.
-
-
0下载:
是学习PCA特征提取的很好的学习资料,包括面积、周长、矩形度、伸长度,多元数据分析的主分量分析投影。- Is a good learning materials to learn PCA feature extraction, Including the area, perimeter, rectangular, elongation, Principal component analysis of multivariate data analysis projection.
-
-
0下载:
是学习PCA特征提取的很好的学习资料,主同步信号PSS在时域上的相关仿真,多元数据分析的主分量分析投影。- Is a good learning materials to learn PCA feature extraction, PSS primary synchronization signal in the time domain simulation related, Principal component analysis of multivariate data analysis p
-
-
0下载:
基于核的主成分分析是一种非线性特征提取方法,它通过一个非线性映射将数据从输入空间映射到特征空间,然后在特征空间中进行通常的主成分分析,其中的内积运算采用一个核函数来代替-Core-based principal component analysis is a nonlinear feature extraction method, which maps data the input space to the feature space through a nonlinear mapping,
-
-
0下载:
music高阶谱分析算法,包括主成分分析、因子分析、贝叶斯分析,是学习PCA特征提取的很好的学习资料。- music higher order spectral analysis algorithm, Including principal component analysis, factor analysis, Bayesian analysis, Is a good learning materials to learn PCA feature extraction.
-
-
0下载:
用于图像识别和特征提取时的主成分分析程序,采用Matlab编写,-When used in image recognition and feature extraction of principal component analysis procedure, using Matlab,
-
-
0下载:
用于图像识别和特征提取时的主成分分析程序,采用Matlab编写,-When used in image recognition and feature extraction of principal component analysis procedure, using Matlab,
-
-
0下载:
用于图像识别和特征提取时的主成分分析程序,采用Matlab编写,-When used in image recognition and feature extraction of principal component analysis procedure, using Matlab,
-
-
0下载:
PCA源程序,主元分析源程序,可以用于变量的特征提取(PCA source code, principal component analysis source, can be used for variable feature extraction)
-
-
0下载:
PIVlab - 时间分辨粒子图像测速(PIV)工具:
一种基于GUI的工具,用于预处理,分析,验证,后处理,可视化和模拟PIV数据。
使用MATLAB网络研讨会进行人脸识别代码:
使用MATLAB在线讲座的人脸识别中的主要演示文件。
Gabor特征提取:
该程序生成一个自定义Gabor滤波器组; 并使用它们提取图像特征。
主成分分析:
用于特征提取;
链码:
基于MATLAB的freeman的曲面轮廓描述(PIVlab - time resolved particle
-
-
0下载:
用于图像识别和特征提取时的主成分分析程序,采用Matlab编写,(When used in image recognition and feature extraction of principal component analysis procedure, using Matlab,)
-
-
0下载:
Principal component analysis of multivariate data analysis projection, PSS primary synchronization signal in the time domain simulation related, Is a good learning materials to learn PCA feature extraction.
-
-
0下载:
Weighted acceleration, It draws on principal component analysis algorithm (PCA), For feature extraction, signal de-noising.
-
-
0下载:
Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Principal component analysis of multivariate data analysis projection, For feature extraction, signal de-noising.
-
-
1下载:
主成分分析的一种改进算法,是一种非线性的特征提取方法。(An improved algorithm of principal component analysis is a nonlinear feature extraction method)
-