gps-signal-autocorrelation

设计一个IIR数字低通滤波器， 逼近一组模拟滤波器的指标参数（通带截止频率Wp=2*pi*2000rad/s,阻带边界频率Ws=2*pi*3000rad/s,通带波纹 Rp=3db, 阻带衰减Rs=15db, 采样频率f=10000Hz）； 分别用脉冲响应不变法和双线性变换法实现设计，列出传递函数并描绘模拟和数字滤波器的幅频和相频响应曲线。用上述设计滤波器完成几组给定信号的滤波，证明滤波器的有效性和滤波范围限制.(Design a IIR digital low-pass filter, approaching a group of analog filters indicator parameters (pass-band cut-off frequency Wp = 2* pi* 2000rad/s, stop-band edge frequency Ws = 2* pi* 3000rad/s, pass-band ripple Rp = 3db, stop-band attenuation Rs = 15db, the sampling frequency f = 10000Hz) were used to change the impulse response method and bilinear transformation method for design, list and describe the transfer function of analog and digital filter amplitude-frequency and phase-frequency response curve. A filter was designed with the completion of the above-mentioned groups of a given signal filtering, to prove the effectiveness of filters and filter limit)

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.

用matlab实现非线性支持向量机分类器对多类进行分类。(Using matlab to achieve non-linear support vector machine classifier for multi-class classification.)

此程序包含求任意点高斯积分节点和对应的Gauss的求解系数(同时也编写了Lagrange插值公式)(for this procedure include arbitrary point Gaussian integral node and the corresponding Gauss coefficient of the solution (also prepared Lagrange interpolation formula))

surf特征点检测，并实现两幅图像特征点的匹配(surf feature point detection, and the two images matching feature points)

Python script to generate prime numbers.

Sodoku Solver in matlab.

说明：  在matlab环境下图像加上噪声然后用中值滤波方式去除噪声(Image in matlab environment with noise and then median filtering method to remove noise)

synchronisation impulsive satllite

ja磁滞模型下无磁滞效应磁化强度曲线的仿真( Simulation of magnetization curve without hysteresis effect )