[MATLAB].David.McMahon

用Matlab实现的图像边缘检测和分割的应用程序(Using Matlab to achieve the image edge detection and segmentation applications)

这是个跨平台的英文学习书籍，希望更多的人使用wxwidget来用C++，大家可以一起使用与讨论(This is a cross-platform study of English books, I hope more people use wxwidget to use C++, we can all use and discussion)

用Levinson算法，Burg算法，ARMA模型法，MUSIC算法来估算功率谱。并进行比较。(With Levinson algorithm, Burg algorithm, ARMA model method, MUSIC algorithm to estimate the power spectrum. And compared.)

日本九州大学的机械工程学院的 Xiong Xiaogang 于 2012 年提出一种更易于实现、同时有能够描述所有摩擦力现象的摩擦力模型，其基于一个微分方程和两个代数方程。本程序是其Simulink实现，非常好用。模型原理请参考：(In 2012, Xiong Xiaogang of the school of mechanical engineering, Kyushu University, Japan proposed a much easier way. The friction model, which can describe all friction phenomena, is based on a differential equation and two algebraic equation. This program is its Simulink implementation, very good use. Model principles, please refer to:Xiong X, Kikuuwe R, Yamamoto M. A differential-algebraic multistate friction model[M]. Simulation, Modeling, and Programming for Autonomous Robots. Springer Berlin Heidelberg,2012)

基于matlab的一维时域有限差分程序，使学习时域有限差分方法的好资料。(Matlab-based one-dimensional finite difference time domain procedure, so that learning FDTD good information.)

a package about mimo toolbox in matlab

用自适应门限的方法进行跳频信号的参数估计，取得了较好的效果(Adaptive threshold method estimates the parameters of frequency hopping signals, achieved good results)

假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。 在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。 (Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality )

用MATLAB实现模式识别中的贝叶斯分类(Using MATLAB to achieve recognition in the Bayesian classifier)

#include "comparer.h" #include <iostream> using namespace std int Comparer::compareByName(Student& s1,Student& s2) { return strcmp(s1.m_szName,s2.m_szName) } int Comparer::compareBySurname(Student& s1,Student& s2) { return strcmp(s1.m_szSurname,s2.m_szSurname) } int Comparer::compareByGroup(Student& s1,Student& s2) {