ga-for-tsp

设计一个2阶加权自适应噪声对消器，对经加性白高斯噪声信道干扰的正弦信号进行滤波(The design of a 2-order-weighted adaptive noise cancellation, and for the AWGN channel interference filtering of sinusoidal signals)

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) )

一个较为广泛的离散小波变换的实现方法，值得新手练习使用。(A more extensive implementation of discrete wavelet transform, worth novice practice use.)

依据感应电机实际参数，利用MATLAB的M函数编写程序，并进行实际的仿真(Based on the actual parameters of the induction motor using MATLAB M-function programming, and the actual simulation)

说明：  wavefront Zernike calculation

Sample Echo Removal Code for Matlab

智能优化算法matlab程序实现，包含各种算法的程序代码(Intelligent optimization algorithm matlab program )

这里面是我最近下载的所有的差分进化和NSGA2的代码，还有个很好用的NSGA2和DE的结合。(There is all the difference in the evolution and NSGA2 I recently downloaded the code, there is a good use of a combination of NSGA2 and DE.)

Tournoment selection

自己收集的一点资料，特别是如何在matlab中实现滤波器设计(Own collection of little information, especially how to implement filter design matlab)