findpeaks

单纯形优化算法可以很好的得到想要的结果哦，速度还可以(danchunxing)

Matlab入门,非常好的资料,对于初学者尽快熟悉运用是个不错的帮手(Matlab entry, very good information for beginners as familiar with the use is a good helper)

波束成形在多天线MIMO环境下的，接收端合并与检测技术(Under the multi-antenna beamforming MIMO environment, merged with the receiver detection technology)

By evaluating its performance through computer simulations for various channels(it suitable for high-speed channel equalization.)

A fast customizable function for locating and measuring the peaks in noisy time-series signals. Adjustable parameters allow discrimination of "real" signal peaks from noise and background. Determines the position, height, and width of each peak by least-squares curve-fitting.(A fast customizable function for locating and measuring the peaks in noisy time-series si gnals. Adjustable parameters allow discrimin ation of the "real" signal peaks from noise and back ground. Determines the position, height, and width of each peak by least-squares curve-f itting.)

基于Matlab simulink搭建的方波逆变器仿真模型，模型正确可直接使用(Square wave inverter simulation model based on Matlab simulink structures, the model is correct and can be used directly)

信息论与编码作业,里面是信息论与编码的作业啊(Information theory and coding jobs, which is information theory and coding jobs ah)

Bayesian classifier experimental pattern recognition programs used in the experimental program

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) )

关于矢量控制仿真模型，大家可以参照做自己的模型(On vector control simulation model, we can refer to do his own model)