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说明：  多变量内模模糊控制程序，将内模控制与模糊控制结合起来，实现更好的控制效果。(Multi-variable fuzzy internal model control procedures, the internal model control and fuzzy control combined to achieve a better control effect.)

MATLAB FUZZY BASIC OPERATIONS

1: MSE.m : to perform Mean Square Error between 2 images 2: most.m : to get the most redundant value in a matrix 3: getneighbors.m : to get circular neighbors of pixel 4: ColorSpaceConversion.m : convert an image into different color spaces and shows their channels 5: ImageSlicer : to separate the 8 bit planes of an image(return m*n*8 matrix) 5:

说明：  该模型描述的是三相异步电机的数学模型，主要是基于MTALAB中的Simulink来创建的，对于电力同学有极大用处。(The model describes the three-phase induction motor mathematical model is based mainly on MTALAB in Simulink to create, students will have great utility for electricity.)

图像跟踪中的meanshift算法，通过MATLAB实现，有注释(Meanshift image tracking algorithm, MATLAB implementation, there is a comment)

利用python实现基于用户的协同过滤推荐，采用pearson相关系数计算相似度，加权平均预测分数(Users use python-based collaborative filtering recommendation, pearson correlation coefficient is calculated using the similarity, the weighted average prediction scores)

For using this code need to use signal toolbox and general toolbox in your matlab Inpainting using sparse regularization. Consider the pepper image with many missing pixels. Assume that the image is noisy-free. (a) Inpaint the image by using orthogonal wavelet sparsity. (b) Inpaint the image by using a different sparsity prior. Based on the outputs, it is clear that the inpainting result obtain by Sobolev is much better than other methods (i.e. Orthogonal wavelet sparsity and Invariant wavelet sparsity).

利用matlab写成的窄带噪声发生，最小均方误差（MMSE）的算法，ML法能够很好的估计信号的信噪比。( Using matlab written narrowband noise occurs, Minimum mean square error (MMSE) algorithm, ML estimation method can be a good signal to noise ratio.)

说明：  按照全赛一等奖论文中叙述的算法编写，含有C和MATLAB两种程序(In accordance with the competition the first prize paper describes an algorithm written in MATLAB with C, and two procedures)

matlab高级编程 课本中的源代码 作者谷源涛(" Matlab Advanced Programming," in the source code for textbook authors Gu Yuan Tao)