BPneuralnetwork

一个PSO算法历程，有详细的注释，及相关演示过程。采用了基本PSO、权重优化、最大速度法三种（去掉代码中的相关行的注释即可使用）。(PSO algorithm is a process, detailed notes, and related presentation process. With the basic PSO, weight optimization, the maximum speed law of three (remove the code related to the comment line can be used).)

A matlab example for the datareader

receiver for vblast

电力电子电路单相桥式全控整流电路的simulink仿真(Power electronic circuit single phase bridge rectifier circuit with Simulink simulation)

THREE PHASE DYNAMIC VOLTAGE RESTORER WITH VOLTAGE SWELL CONDIDTIONS

Matlab Edge detection using masks

Optimal Component Selection Using Mixed-Integer Genetic Algorithm

估算带宽，先是计算输入信号单边带功率谱密度，然后估算出信号所占的带宽(Bandwidth estimation, first calculating the input signal is single sideband power spectral density, and then estimate the proportion of signal bandwidth)

synchronous genertor with PV array

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) )