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PCADR
说明： 用于特征降维人脸识别等多元数据分析的主分量分析投影的Matlab代码实现。(For feature reduction and other multivariate data analysis, face recognition principal component analysis projection of the Matlab code implementation.)
- 2010-04-10 14:28:49下载
- 积分：1
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Optragen-master
说明： Matlab toolbox for parsing optimal control problems into nonlinear programming problem. Please read the documentation under subdirectory manual. There are a few examples that should help you get started.
- 2020-06-04 23:27:07下载
- 积分：1
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dsp5
说明： 利用matlab强大的数据处理功能和图形化功能来对信号进行处理，这是吴镇扬的数字信号处理第五次实验的全部代码，可用来参考(Using matlab powerful data processing and graphical capabilities of signal processing, which is the fifth digital signal processing Zhen-Yang Wu experiment all of the code can be used to refer to)
- 2011-03-27 15:20:43下载
- 积分：1
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exm1
基本的MATLAB界面设置,未说到具体M编程和调试(The basic MATLAB interface settings, not when it comes to specific programming and debugging M)
- 2013-12-17 10:48:04下载
- 积分：1
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PCA
用主成分分析法估计出点云中每点的法向量函数(Principal component analysis method for normal estimation in point cloud )
- 2020-07-31 16:28:37下载
- 积分：1
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K-meanCluster
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)
- 2007-11-15 01:49:03下载
- 积分：1
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2222
基于CCD图像采集系统的处理和研究，研究CCD的文章，不错(CCD image acquisition system based on the treatment and research, research articles CCD, it is true)
- 2008-01-25 17:02:18下载
- 积分：1
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diancichangfangzhen
电磁波与电磁场的仿真，其中有平行双导线，同轴线电位仿真程序及仿真结果。(Electromagnetic waves and electromagnetic field simulation, parallel twin wire, coaxial potential simulation program and simulation results.)
- 2013-05-05 13:55:23下载
- 积分：1
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houghline
matlab实现hough变换直线提取，不直接用hough算子，应用二值化图像(to achieve a straight line hough transform matlab extraction, does not directly hough operator, the application of binary image)
- 2009-06-05 23:28:47下载
- 积分：1
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cute
Display symbolic expression in web browser
- 2011-08-31 08:51:31下载
- 积分：1
