3L-IBS

计算LP01模式分布，对于光学的传输模式的把握和分析能器到很大的作用(Calculate the distribution of LP01 mode, the transmission mode for the optical analysis can grasp and very useful device to)

适合大家的学习滑模变算法，刘金琨老师书上的例子。(Sliding Mode algorithm suitable for all learning, Liu Jinkun teacher book example.)

信号模拟，分析以及应用可以分析波形的变换，频率周期的转换等。(Ocean Wave Theory of Physical Oceanography hydrodynamic theories programming model)

3维FDTD程序,非常实用的一个MATLAB程序，适用于任何三维结构，分享给大家使用。(Three-dimensional FDTD program, a very practical MATLAB procedures applicable to any three-dimensional structure, to share for everyone to use.)

动态模型参数的极大似然辨识及其MATLAB实现范例(Dynamic model parameters of maximum likelihood identification and implementation examples of MATLAB)

u can calculate DCT clc inp = imread( Im1.jpg ) inp1 = imread( Im2.jpg ) A = double(inp(:,:,1)) B = double(inp1(:,:,1)) A1=double(blkproc(A,[8 8], dct2 )) B1=double(blkproc(B,[8 8], dct2 )) [r,c] = size(A1) r1 = [] for i=1:r for j=1:c if A1(i,j) > B1(i,j) r1(i,j)=A1(i,j) else r1(i,j)=B1(i,j) end end end r1= double(r1(:,:,1)) C=blkproc(r1,[8 8], idct2 ) round(C) C1=idct2(r1) figure imshow(uint8(C)) figure imshow(uint8(C1)) imwrite(uint8(C), dct8x8min.jpg )

说明：  是matlab语言，对阶跃折射率分布锥形光纤模型中的光场分布进行了模拟。 (Is the matlab language, on the step refractive index distribution of tapered fiber-optic model of optical field distribution are simulated.)

说明：  计算模糊C-均值聚类中的初始隶属度值，并进行调节(clculate the initial degree of membership)

用于认知无线电能量检测及频谱感知的matlab程序(Used for cognitive radio energy spectrum of detection and perception of matlab)

机器学习中的垃圾邮件分类程序，用matlab做的。从以下链接下载垃圾邮件数据（spam data）：(数据已下载，放在spambase.zip) http://www-stat.stanford.edu/~tibs/ElemStatLearn/index.html 该数据包含57个邮件信息相关的变量，每条邮件可以被分类为垃圾邮件（Y=1）和非垃圾邮件（Y=0）。输出Y的值在文件中每一列的末尾。练习的目标是要预测电子邮件是否为垃圾邮件。 (Machine Learning spam classification procedures, using matlab to do. Data (spam data) from the following link to download the junk mail: (data has been downloaded, put spambase.zip) http://www-stat.stanford.edu/ ~ tibs/ElemStatLearn/index.html The data includes 57 e-mail messages related variables, each message can be classified as spam (Y = 1) and non-spam (Y = 0). Y value of the output end of each column in the file. The goal is to predict exercise email is spam.)