搜索资源列表
matlab-uniquac.rar
- 本程序使用matlab语言,编制了一个基于通用似化学活度系数模型来计算四组分反应体系中各组分的汽液平衡状态的程序.,This procedure using the matlab language, developed a chemical based on a common activity coefficient model seems to calculate the four-component reaction system of the components of the vapor
Component-extraction
- Component-extraction.rar实现彩色图像的RGB三分量的提取，并将各个分量图像进行均衡化-Component-extraction.rar to achieve color image of RGB three-component extraction, and the various component images equalization
matlab-pca
- 这是一个主成分分析的matlab程序，非常有用。-This is a principal component analysis of matlab procedures, very useful.
Matlab
- 模拟退火算法实现、主成分分析实现及线性回归分析等-Simulated annealing algorithm implementation, implementation of principal component analysis and linear regression analysis
Matlab
- Matlab数据统计和分析的程序，包含下面所列的多种算法的 MultiLineReg 用线性回归法估计一个因变量与多个自变量之间的线性关系 PolyReg 用多项式回归法估计一个因变量与一个自变量之间的多项式关系 CompPoly2Reg 用二次完全式回归法估计一个因变量与两个自变量之间的关系 CollectAnaly 用最短距离算法的系统聚类对样本进行聚类 DistgshAnalysis 用Fisher两类判别法对样本进行分类 MainAnalysis 对样本进行主成分
PCA-matlab
- 里面包含主元分析PCA的Matlab代码，包括提取主元，求方差贡献率，绘制贡献率直方图等-Which contains the principal component analysis PCA of the Matlab code, including the extraction of the main element, seeking variance contribution rate, contribution rate of histogram mapping, etc.
matlab
- 如何在matlab下做的com组件，然后在vb,c#.net，vc实现调用然后打包-Matlab how to do so under the com component, and then in vb, c#. Net, vc call and then packaged to achieve
FICA-matlab
- fast fixed-point algorithm -The FastICA package is a free (GPL) MATLAB program that implements the fast fixed-point algorithm for independent component analysis and projection pursuit. It features an easy-to-use graphical user interface, and a comput
chengxu
- 本程序应用了取两次阈值、基于特征的逻辑、二值形态学和相连成分的标识，确定了钢的显微图像中颗粒的边界，标识了不同的颗粒。-This procedure applies to take the two threshold values, based on characteristics of logic, binary morphology and connected component labeling, to determine the microstructure of steel grain
matlab
- ) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。-) The use of sub-blocks of principal component analys
licenseplatelocation
- 一种多车牌定位方法，该方法综合利用边缘检 测、连通域分析、倾斜矫正等多种方法,解决了复杂背景中定位难的问题-A multi-plate location method, which combined with an edge detection, connected component analysis, tilt correction and other methods to solve the complex problem of difficulties in the context
bw-Noise-Reduction
- 这个函数获取二进制图像，然后根据图像中标记目标的连接性和每个连接组成的像素数量来判断是否是噪声。 -The function to get the binary image, then image tag target connectivity and the number of pixels of each connected component to determine whether it is noise.
Principal-component-analysis-matlab
- 主成分分析.mht：介绍主成分分析的文章 edgepick.m：本程序的目的是实现边缘检测 drawprim.m：找到最大主分量所在的位置，从而在原图象中绘出 practical.m：一个主分量的程序，边缘检测和主分量提取 prin.m：该程序是用princomp函数来提取矩阵的主成分-Principal component analysis. Mht: the article describes the principal component analysis edgepick
Connected-component-labelling-by-an-Iterative-alg
- Connected component labeling by an Iterative algorithm used for labeling image pixel.It will divide the region according to pixel value.
MATLAB
- matlab 滤波信号处理功能，消除确定性成分和拟合曲线。-matlab funtionFiltering signal processing function, eliminate deterministic component and fitting curve 。
Face-Recognition-By-MatLab
- Principle component Analysis based face recognition system
Morphological-threshold-segmentation
- 实现形态学的阈值分割，可得到分割后的阈值图像，形态学图像，L的直方图，最大连通成分提取图像以及最后得出的结果图像。-Achieve morphological thresholding, the threshold obtained after image segmentation, image morphology, L histogram, the largest connected component extraction result image and the final image.
Matlab-component--in-Optisystem
- Matlab component,Creating a component to handle optical signals in Optisystem -In order to create an optical component in Matlab for co-simulation with OptiSystem, first we need to understand the optical signal format that OptiSystem can generate and
Fourier descriptors using matlab
- The descr iptors c(k) describe the frequency contents of the curve: a value of k close to zero will describe low frequency information, an approximative shape, and the higher frequencies will describe details. For k = 0, c(k) represents the position
基于信息熵的约简MATLAB代码
- 利用matlab和ceemd进行编程求解简单的信息熵，根据求解的imf分量判断信号的情况(Using MATLAB and ceemd programming to solve simple information entropy, according to the IMF component to determine the situation of the signal)