menxian

Matlab环境下，进行二维空间波动方程的模拟。吸收边界条件(Matlab environment, the wave equation for two-dimensional simulation. Absorbing boundary conditions)

针对H无穷大控制，附加Matlab程序，进行解说，英文原文(For H infinity control, additional Matlab procedures explained, the original English text of)

基于VB／MATLAB的前兆资料小波分析程序的实现(Based on the VB/MATLAB wavelet analysis of the precursor process information to achieve)

考虑L的三个不同值：L＝256（3个数据段），L＝128(7个数据段)和L=64（15个数据段）。各自的谱估计图如上图所示。可以明显的看到，加窗明显的减小了频谱上的假谱峰，但也更加进一步平滑了谱峰。所以，对于L＝64的情况，在ω＝0.8π的谱线可以很确定的辨认，但是那两个靠近的谱峰不容易区分。对于L＝128的情况，这种情况提供了在分离和检测间最好的均衡。当然，对于在L＝256时的情况，效果是更好的，能够从谱估计图上明显的分辨出三条谱线的存在以及它们幅度关系的强弱。 除了Welch法外，还可以采用对多个周期图求平均的功率谱估计方法的其他方法如Bartlett法等等，在功率谱估计上也能取得较好的结果。(consider three different values : L = 256 (3 data), L = 128 (7 data) and L = 64 (15 data). Their spectral estimation map as shown in Fig. It is clear to see that increase significantly decreasing window of the spectrum of false peaks, but much more to further smooth the peaks. Therefore, L = 64, in the case = 0.8 spectrum can determine the identification, but that the two peaks around is not easy to distinguish. L = 128 for the situation, which provided the separation and detection among the best balanced. Of course, L = 256 in the case, the effect is better, from the spectral estimation map clearly distinguish between the three lines of the existence and their relationship to the rate of strength. In addition to Welch law, but also can be used to map multiple cycle for the average power)

基于RA码的信道编码与物理层网络编码联合设计仿真程序(Based on the physical layer channel coding and network coding RA joint design simulation program code)

基于相位调制器产生六倍频光毫米波的 OFDM信号光传输系统研究 (A Radio Over Fiber System with Frequency Sextuple Optical Millimeter
Wave Generation Carrying OFDM Signal Utilizing Phase Modulator)

里面包含了，灰色模型的matlab代码，以及改进的指数预测算法，李顺等人的预测算法，适合于简单的预测(Contains inside, grey model of matlab code, and improving the index prediction algorithm, Li Shun et prediction algorithm, is suitable for simple prediction)

解耦PID控制器，常用于工业过程控制 ，与各位分享，谢谢大家。(Decoupling PID controller, commonly used in industrial process control, to share with you, thank you.)

clear all I=imread( lena.bmp ) figure imshow(I) I2=imrotate(I,-4, bilinear ) 逆时针旋转4度 figure imshow(I2) I3=fliplr(I) 垂直镜像 figure imshow(I3) I4=imresize(I,0.5, bilinear ) 缩小为原图的1/2 figure imshow(I4) A=double(I) 转换为double类型 计算7个不变矩 [nc,nr]=size(A) [x,y]=meshgrid(1:nr,1:nc) 得到网格 x=x(:) y=y(:) A=A(:) m.m00=sum(A) if m.m00==0 m.m00=eps end m.m10=sum(x.*A) m.m01=sum(y.*A) 计算均值 xmean=m.m10/m.m00 ymean=m.m01/m.m00 计算中心矩(li9_23.rar cm.cm00=m.m00 cm.cm02=(sum((y-ymean).^2.*A))/(m.m00^2) cm.cm03=(sum((y-ymean).^3.*A))/(m.m00^2.5) cm.cm11=(sum((x-xmean).*(y-ymean).*A))/(m.m00^2) cm.cm12=(sum((x-xmean).*(y-ymean).^2.*A))/(m.m00^2.5) cm.cm20=(sum((x-xmean).^2.*A))/(m.m00^2) cm.cm21=(sum((x-xmean).^2.*(y-ymean).*A))/(m.m00^2.5) cm.cm30=(sum((x-xmean).^3.*A))/(m.m00^2.5) im(1)=cm.cm20+cm.cm02 im(2)=(cm.cm20-cm.cm02)^2+4*cm.cm11^2 im(3)=(cm.cm30-3*cm.cm12)^2+(3*cm.cm21-cm.cm03)^2 im(4)=(cm.cm30+cm.cm12)^2+(cm.cm21+cm.cm03)^2 im(5)=(cm.cm30-3*cm.cm12)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm21-cm.cm03)*(cm.cm21+cm.cm03)... +(3*(cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2) im(6)=(cm.cm20-cm.cm02)*((cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2)... +4*cm.cm11*(cm.cm30+cm.cm12)*(cm.cm21+cm.cm03) im(7)=(3*cm.cm21-cm.cm03)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm12-cm.cm30)*(cm.cm21+cm.cm03)... *()

[hao]超宽带通信系统的Simulink仿真实现,较好的利用了matlab平台([hao] Ultra-Wideband Communication Systems Simulink simulation of the realization of a better platform to use the matlab)