DVB-T

里面有对img格式文件的读取方式，还有对图像进行低通和高通滤波的方法。(There is on img file format, and read the image low-pass and high-pass filter method.)

基于2阶消失矩的Daubechies尺度函数的TE波2维MRTD仿真，吸收边界条件为FDTD/PML连接边界。(2D MRTD TE mode baseed on 2nd-vanishing moments of Daubechies scaling function simulation, the absorbing boundary condition is FDTD/PML connection boundary.)

網路上找到簡單的車牌定位，有需要可以看看(License plate location to find on the Internet)

通过pca找点云主方向，确定新坐标，然后将旧坐标点投影新坐标(Coordinate transformation using Principal Component Analysis)

通过matlab/simulink平台,得到IEC电压波动和闪变现象的仿真模型(The simulation model of voltage fluctuation and flicker of IEC is obtained through the matlab/simulink platform)

quadrature amplitude modulation

homework 3-5 is difficult

Butterworth滤波原代码程序，目标跟踪。(target tracking)

说明：  蚁群算法，蚁群算法，蚁群算法实例蚁群算法，蚁群算法，蚁群算法实例蚁群算法，蚁群算法，蚁群算法实例蚁群算法，蚁群算法，蚁群算法实例蚁群算法，蚁群算法，蚁群算法实例蚁群算法，蚁群算法，蚁群算法实例(Ant algorithm, ant algorithm, ant colony algorithm instance ant algorithm, ant algorithm, ant colony algorithm instance ant algorithm, ant algorithm, ant colony algorithm instance ant algorithm, ant algorithm, ant colony algorithm instance algorithm, ant algorithm, ant colony algorithm instance ant algorithm, ant algorithm, ant colony algorithm instance)

功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。(Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe)