ThresGUI

说明：  车牌倾斜校正程序，将车牌边界与图像边界不平行的图像进行旋转，使其平行，可用于车牌识别。(Plate tilt correction procedure, the plate boundary is not parallel with the image border to rotate the image, a parallel can be used for license plate recognition.)

现有一个信号：x(n)=1+cos(π*n/4)+ cos(2*π*n/3)设计及各种数字滤波器以达下列目的： 低通滤波器，滤除cos(2*π*n/3) 的成分，即想保留的成分为1+cos(π*n/4) 高通滤波器，滤除1+cos(π*n/4) 的成分，即想保留的成分为cos(2*π*n/3) 带通滤波器，滤除1+cos(2*π*n/3) 的成分，即想保留的成分为cos(π*n/4) 带阻滤波器，滤除cos(π*n/4) 的成分，即想保留的成分为1+cos(2*π*n/3) 1. 用MATLAB命令butterord求除滤波器的阶数,用命令butter设计各滤波器；画出滤波器幅度和相频相应 取各滤波器的系统函数H(z)。 (an existing signal : x (n) = a cos (* n/4) cos (2** n/3) design and digital filter to achieve the following objectives : low-pass filter, filter cos (2** n/3) the ingredients that want to retain an element of a cos (* n/4) high-pass filter, a filter cos (* n/4) components, namely to retain the element of cos (2** n/3) band-pass filter , a filter cos (2** n/3) components, namely to retain the element of cos (* n/4) band stop filter, the filter cos (* n/4) components, namely to retain the ingredients for a cos ( 2** n/3) 1. MATLAB order butterord except for the band Filter, using the order of the filter design butter; paint Filter magnitude and phase frequency of the corresponding filter system function H (z).)

GPS接收系统中信号的组成 CA码的产生(GPS receiver of c/a code)

负正弦加白噪声随机过程下使用MUSIC方法进行信号频率估计仿真，信号样本数去1000，估计的自相关矩阵为8阶，分别采用AIC和MDL准则估计信号源个数，并画出相应的MUSIC频率估计谱线。(Negative sine plus white noise random process method using MUSIC frequency estimation simulation, signal samples to 1000, the estimated autocorrelation matrix of order 8, AIC and MDL criteria were used to estimate the number of signal sources, and draw the corresponding MUSIC frequency spectrum estimation.)

hi this about simulation of ecg signals

说明：  关于数字信号处理的matlab小作业。初学者可以看看。高手就算了。。。。(Matlab on a small digital signal processing operations. Beginners can look at. Even the master. . . .)

histogram image for image processing

simulation of a channel using BPSK and QPSK

信号与系统基础练习，演示了数字信号处理中常用的傅里叶变换，分析时域和频域的信息(Signals and systems based practice, demonstration of digital signal processing used in the Fourier transform of the time domain and frequency domain information analysis)

最小二乘支持向量机，程序粘到command window里，设定 2 两个参数，可以更改，以达到最优化(igam=0.001 isig2=0.001 [gam,sig2]=tunelssvm({X,Y, f ,igam,isig2, RBF_kernel },... [0.001 0.001 10000 10000], gridsearch ,{}, leaveoneout_lssvm ) type= function approximation kernel= RBF_kernel model=initlssvm(X,Y,type,gam,sig2,kernel) model model=trainlssvm(model) Yt=simlssvm(model,Xt) )