DEA-Matlab

非常好的一篇硕士论文 针对2 1 6卷积码的不同删除码率(Very good a master' s thesis for the 216 rate convolutional codes of different deletion)

this code is tell about segmentation of an image

希尔伯特-黄变换在电力故障中的应用 内含EMD分解 希尔伯特变换算法(Hilbert- Huang transform in power failure in the application)

说明：  非线性有限元程序，二维， 非常好用的啊！！！！！！！！！！！！！！！！！！！！！！！！！！！！(nonliear fem)

均匀球形粒子的Mie理论散射光强计算程序： 1．RB1.m 计算第一类Ricatti-Bessel函数的函数 2．RB2.m 计算第二类Ricatti-Bessel函数的函数 3. Alegendr.m 计算角函数 和 的函数 4. MieCoeff.m 计算米尔系数的函数 5. Amp.m 计算散射光复振幅的函数 6. MieIntensity.m 画均匀粒子散射角-光强图 (Uniform spherical particle Mie theory scattering intensity calculation procedures: 1. RB1.m calculate the first class Ricatti-Bessel function of the function 2. RB2.m calculate the second category Ricatti-Bessel function of the function 3. Alegendr.m computing angle functions and function 4. MieCoeff.m Mill coefficient calculation function 5. Amp.m calculate the scattering amplitude recovery function 6. MieIntensity.m Painting uniform particle scattering angle- light intensity diagram)

悬置功能计算的，能量解耦的方法，优化及其位移的计算(The calculation of suspended function, energy decoupling method, optimization and calculation of displacement)

实现应用VC++读取mat文件，实现VC++与matlab混合编程(Achieve application VC++ to read mat file, to achieve mixed VC++ and matlab programming)

用matlab求图像阈值分析程序，一种是直方图阈值法一种是最大类间方差(Using matlab and image threshold analysis program, a variance between a Histogram method is the largest class)

使用MATLAB软件，应用吉布斯采样方法，对信号进行抽样(use MATLAB)

不错的GM_EM代码。用于聚类分析等方面。( GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres)