KalmanAll

流形学习是近年来机器学习及模式识别等领域的一个研究热点，其主要目标是去发现高维观察数据空间的低维光滑流形。自从2000年Roweis和Saul提出LLE算法、Tenenbaum等人提出Isomap算法，特别是Donoho等人发现Isomap算法能够准确发现人脸图像流形潜在的参数空间、张长水等人将LLE算法用于人脸识别并取得了较好的识别效果之后，基于流形学习的人脸识别研究引起了人们的广泛关注。(Manifold learning in recent years the field of machine learning and pattern recognition as a research focus, its main goal is to find high-dimensional data space observation of low-dimensional smooth manifold. Since 2000 LLE algorithm proposed by Roweis and Saul, Tenenbaum and others proposed Isomap algorithm, especially Donoho, who found that Isomap algorithm can find the potential face images of the parameter space manifold, and Chang-water will LLE algorithm for face recognition and to obtain a good recognition results, the manifold learning-based face recognition research has aroused extensive attention.)

Kalman filter examples, kalman_update

。在总结前人提出的一些锁相环仿真模型的基础上,用Matlab 语言构建了一种新的适用于全 数字锁相环的仿真模型 对全数字锁相环版图进行了SPICE 仿真,与该模型的仿真结果相验证。(. Built using Matlab language summary of some of the previously proposed phase-locked loop simulation model based on a simulation model of a new applicable to all-digital phase-locked loop DPLL layout SPICE simulation, with the The model simulation results verified.)

计算机控制系统5道大题作业，有详细求解过程及相应的matlab程序。(five task of Computer Control System with detail solution and conresponding to matlab programing)

这是一个NSCT的工具箱，用与图像融合等图像处理MATLAB程序。(nsct_toolbox use in image fusion)

MATLAB 工程数学应用,许波,刘征编著(The MATLAB engineering mathematics application, Xu Bo, Liu Zheng eds)

实现对一个信号源的doa估计，非常有用，对初学者很用帮助(Achieve a signal source doa estimation, very useful)

带可调渐消因子的无迹卡尔曼滤波程序MATLAB仿真实例(With adjustable fading factor unscented Kalman filtering procedures MATLAB simulation examples)

在这个实验中，需要输入一个整周期内100个采样点的值，没有利用查找表的方法实现，而是直接在程序中输入100个采样点的值。2FSK/2PSK主要包括两部分2FSK信号发生器和2PSK信号发生器。2FSK信号发生器主要有分频器，m序列产生器，跳变检测，正弦信号发生器和DAC几个部分组成。2FSK的关键是通过判断信号跳变是来改变频率的变化，2PSK的关键是通过信号的跳变来改变相位的变化。(psk)

单步单纯型法，输入为系数矩阵，右端向量，目标函数系数向量，基变量下标，非基变量下标和基变量初始值(Step simplex method, the input for the coefficient matrix, right vector, the objective function coefficient vector, the base variable subscript, superscript and the non-basic variable initial value of base variable)