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介绍了MATLAB工具中的数学工具，是你用MABLAB开发时必不可少的参考书籍啊。(MATLAB tools introduced in the mathematical tools, is when you develop MABLAB indispensable reference books ah.)

说明：  一个 实验报告 用于学习MATLAB 的 我是学习不久写出来的 希望那个能给大家提供帮助(WELL)

procesado de imagen mat lab

说明：  这是用MATLAB设计的云模型代码。多多支持(cloud model)

利用相关的瞬时值通过在工作过程中的逐步调整参数逼近信号的统计特性，实现最优滤波。由此，我们得到一种最常用的算法——最小均方算法，简称LMS算法。(By using the instantaneous value of the correlation operation of the progressive approximation of the statistical properties of the signal to adjust the parameters to achieve optimal filtering. Thus, we get one of the most commonly used algorithms- the minimum mean square algorithm, called LMS algorithm.)

这是GP算法进行遗传规划，里面代码齐全，是matla代码(This is the GP algorithm for genetic programming, which is code complete, the code is matla)

这是wimax标准的ldpc码的译码程序 编码程序在文件夹ldpc_minioffset/matlab中，为matlab的源程序(This is the standard ldpc wimax decoding program code program in the folder ldpc_minioffset/matlab in the source code for the matlab)

采样频率 fs=10000 轴承外环故障信号 fid=fopen( bearingout.dat , r ) 故障 N=1024 xdata=fread(fid,N, int16 ) fclose(fid) xdata=(xdata-mean(xdata))/std(xdata,1) 时域波形 figure(1) plot(1:N,xdata) xlabel( 时间 t/n ) ylabel( 电压 V/v ) db10小波进行4层分解 一维小波分解 [c,l] = wavedec(xdata,4, db10 ) 重构第1～4层细节信号 d4 = wrcoef( d ,c,l, db10 ,4) d3 = wrcoef( d ,c,l, db10 ,3) d2 = wrcoef( d ,c,l, db10 ,2) d1 = wrcoef( d ,c,l, db10 ,1) ( Sampling frequency fs = 10000 bearing outer ring fault signal fid = fopen (' bearingout.dat' , ' r' ) failure N = 1024 xdata = fread (fid, N, ' int16' ) fclose (fid ) xdata = (xdata-mean (xdata))/std (xdata, 1) time-domain waveform figure (1) plot (1: N, xdata) xlabel (' Time t/n' ) ylabel ( ' voltage V/v' ) db10 wavelet decomposition 4 layer one-dimensional wavelet decomposition [c, l] = wavedec (xdata, 4, ' db10' ) 1 ~ 4 reconstructed detail signal d4 = wrcoef (' d' , c, l, ' db10' , 4) d3 = wrcoef (' d' , c, l, ' db10' , 3) d2 = wrcoef (' d' , c, l, ' db10' , 2) d1 = wrcoef (' d' , c, l, ' db10' , 1) )

基于遗传算法的无功优化问题，基于Matlab的遗传算法的编程，简单明了，易懂，是对遗传算法的很好地例程(Reactive Power Optimization Based on Genetic Algorithm)

sepia filter on image sepia.m