TF-analysis

three phases in Matlab

1、不同阶次模拟巴特沃兹滤波器的频率响应 2、根据模拟滤波器指标，设计低通巴特沃兹滤波器 要求通带截止频率 fp = 5kHz, 通带最大衰减 ɑp =2dB， 阻带截止频率 fs= 12kHz, 阻 带最小衰减ɑs =30dB,按照上述指标设计巴特沃兹低通滤波器。 3、给定模拟滤波器，按照不同采样频率设计数字 IIR，观察采样频率对设计结果的影响 已知模拟滤波器传输函数 H(s)为 2 0.5012 ( ) 0.6449 0.7079 H s s s = + + 按照不同采样频率 Fs1=1Hz, Fs2=10Hz 使用脉冲响应不变法将 H(s)转换为 H(z)数字 IIR 滤波器。观察不同采样频率设计得到的数字 IIR 的差异。 4、给定数字 IIR 指标，用脉冲响应不变法设计 IIR。 数字低通滤波器的指标为: 0.2 , 1 , 0.3 , 15 p p s s ω π α ω π α = = = = dB dB ,使用巴特沃 兹滤波器设计数字 IIR。比较采样频率 Fs=1， 2 时设计过程中的模拟滤波器，数字滤波 器的变化。 5、用双线性变换法设计 IIR，并同脉冲响应不变法比较设计的结果。数字滤波器指标要 求如下 0.2 , 1 , 0.3 , 15 p p s s ω π α ω π α = = = = dB dB(1.Grasp the impulse response method and bilinear transformation design IIR filter principle and specific design methods, familiar with double A computer program for designing lowpass, bandpass and highpass IIR digital filters by linear design; 2 . familiar with the design of analog Butterworth filter, master impulse response method and bilinear transformation method to design digital IIR Filter method)

位同步例程源代码，gardener算法的(Bit synchronization routines source code, gardener algorithm)

MATLAB CODE FOR DIGITAL COMMUNICATION

本文对视频运动目标跟踪算法进行研究。在视频运动目标的提取中，介绍常用的图像差分算法、光流算法和主动轮廓模型算法。(In this paper, the video moving target tracking algorithm study. Video moving target in the extraction, the introduction of images commonly used differential algorithm, optical flow algorithm and active contour model algorithm.)

Technical Area pattern classification

说明：  Matlab关于FFT算法的编程及原理详细讲解！(Matlab programming on the FFT algorithm and principle explained in detail!)

matlab design of butterworth lowa pass filter

这是一个comsol转化成matlab程序，可以做出z轴循环，求出感应电量(This is converted into a comsol matlab program, you can make the z-axis loop, find the sensor power)

SURF Features A frequent approach to feature extraction from images is SURF (Speeded Up Robust Features) Codebook You can use the function create_codebook.m to create a codebook with k-means Histograms Write a function that creates histograms of single images by assigning the image features to clusters from the codebook and counting their frequency Object recognition Choose two distinct subsets from the images. Create a codebook from one set