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8Matrix Extension with Symmetry and Its Application to Filter Banks 1001.1117

the signal detection in the MC-CDMA system

积分方程的数值解（matlab代码）利用MATLAB求解积分方程的数值解问题(The numerical solution of integral equations (matlab code))

matlabhow can we use matlab to design a programme for mathe and what we can do for our matlab(how can we use matlab to design a programme for mathe and what we can do for our matlab)

共生矩阵是MATLAB实现，在cooccurrence里有实现方法(Co-occurrence matrix is the MATLAB implementation, there realization in the cooccurrence)

A figure ready to scroll through and play videos. You can also draw any custom graphics on it. (VIDEOFIG(NUM_FRAMES, @REDRAW_FUNC) creates a figure with a horizontal scrollbar and shortcuts to scroll automatically. The scroll range is 1 to NUM_FRAMES. The function REDRAW_FUNC(F) is called to redraw at scroll position F (for example, REDRAW_FUNC can show the frame F of a video). This can be used not only to play and analyze standard videos, but it also lets you place any custom Matlab plots and graphics on top. Jiro posted a great example on the Pick of the Week blog, along with a nice GIF animation so you can see it in motion: http://blogs.mathworks.com/pick/2010/12/10/video-player-for-your-frame-based-processing/ EXAMPLE 1 Place this in a file called "redraw.m": function redraw(frame) imshow([ AT3_1m4_ num2str(frame, 02.0f ) .tif ]) end Then from a script or the command line, call: videofig(10, @redraw) redraw(1) The images "AT3_1m4_01.tif" ... "AT3_1m4_10.tif" are part of the Image Processing Toolbox and there s no ne)

双闭环直流调速系统的仿真 内含mdl文件 另附FUZZY控制器(Double Loop DC Speed System includes mdl file attached FUZZY controller)

灰色预测模型是一种模糊预测算法，可以对信息不完全的或不知发展规律的变量进行预测(Gray prediction model is a fuzzy prediction algorithm, you can not know or incomplete information to predict the development of the law of variable)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

The channel coding toolbox includes: Channel models: Binary, symmetric channel (BSC)...