Neural_PID_control_of_two-tank_water_level_control

说明：  matlab数字滤波器设计,计算出参数便于dsp实现(Matlab digital filter design parameters calculated to facilitate achieving dsp)

说明：  PNN的程序，经过验证的，很好使，希望对大家有所帮助！(PNN procedure, proven, well so, we want to help! )

Parse the device s DT node for an endianness specification.

截取一段音频信号作为输入信号，分别通过低通，高通和带通滤波器，比较滤波效果。(Interception of an audio signal as an input signal, respectively, through a low pass, high pass and band-pass filter, compare filtering effect.)

说明：  发射分集alamouti编码，并与无分集时比较，有明显性能提高(Alamouti coding transmit diversity, and diversity when compared with no, there are clear performance improvement)

带电粒子在非匀强磁场中运动时，画出其轨迹图形(Charged particle moving in an inhomogeneous magnetic field when the draw its trajectory graphics)

Pipelined Chebyshev Functional Link Artificial Recurrent Neural Network for Nonlinear Adaptive Filter

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)... *()

This matlab program will detect the largest connected component

EMD matlab程序，附测试数据，通过对高频信号的分解和趋势分析，可实现对数据分析和预测功能。(EMD matlab code)