matlab-5

一个matlab编写的robot demo程序，解压后，运行m文件即可，可看到RPP robot的轨迹。(Matlab prepared a robot demo program, unzip, run the m file you can see the tracks of RPP robot.)

说明：  matlab下进行图像超精度重构，在频域中计算图像间的相互位移，然后再重构(matlab under the ultra-precision image reconstruction, in the frequency domain calculation of the mutual displacement between images, and then remodeling)

programa de editar fotografias

半监督LDS算法,是由Olivier Chapelle提出来的，他将半监督的流行假设和聚类假设结合起来。 (LDS for Semi-supervised learning，which is proposed by Olivier Chapelle,it combinations the monifold assumption and cluster assumption.)

运用平均差-标准差方法，对数据进行金标准分析。( Using mean difference- the standard deviation method, the gold standard for analysis of the data.)

改程序为《自适应信号处理》（Bernard Widrow著，王永德等译）书中101页上图牛顿法的MATLAB程序，仿真效果和书上一致 (Change the program to " Adaptive Signal Processing" (Bernard Widrow a, s Acoustic other translation) book 101 on the map Newton MATLAB programs, simulation results and the same book)

matlab 50道练习题，有助于新手快速提高编程和应用能力(matlab 50 道 exercises to help novice programming and ability to rapidly improve)

A Guide to MATLAB Object-Oriented Programming - Andy H. Register

本例为AR（1）过程的Kalman滤波估计，方法简单，结果比较准确。(In this case AR (1) process, Kalman filter estimation method is simple and the results more accurate.)

An implementation of Unscented Kalman Filter for nonlinear state estimation. (Nonlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded formulation for nonlinear state estimation. However, it may cause significant error for highly nonlinear systems because of the propagation of uncertainty through the nonlinear system. The Unscented Kalman Filter (UKF) is a novel development in the field. The idea is to produce several sampling points (Sigma points) around the current state estimate based on its covariance. Then, propagating these points through the nonlinear map to get more accurate estimation of the mean and covariance of the mapping results. In this way, it avoids the need to calculate the Jacobian, hence incurs only the similar computation load as the EKF. For tutorial purpose, this code implements a simplified version of UKF formulation, where we assume both the process and measurement noises are additive to avoid augment of state and a)