fkmig

matlab光谱预处理之光谱平滑，包括移动平滑及SG平滑(Spectral smoothing of MATLAB spectral pretreatment, including moving smoothing and SG smoothing)

一种基于脉冲耦合神经网络的第三代人工神经网络的边缘检测算法，速度比较快(Based on Pulse Coupled Neural Network' s third-generation artificial neural network edge detection algorithm, the speed is faster)

Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.

说明：  APA基本算法，变步长的，仿射投影算法大作业，文档有说明(APA basic algorithm, variable step size, affine projection algorithm large assignments, documentation)

MATLAB中进行关于智能车的PID参数调节例程.(MATLAB, on the smart car to adjust PID parameters of routine.)

matlab宝典.pdf 学习matlab的好资料(matlab Collection. pdf good information to learn matlab)

本程序为模糊聚类算法在图像分类中的应用。（图像的大小为30*30）。(This procedure for the fuzzy clustering algorithm in image classification applications. (Image size is 30* 30).)

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) )

Matlab code for LPC analysis

采用bpsk调制的直扩通信系统的误码率仿真。可以直接运行，方便初学者使用。(BER modulation using bpsk DSSS communication system simulation. Can be directly run, easy for beginners to use.)