Matlab-DIPUM

matlab学习教程，包括matlab软件基本操作以及对数据的处理，对图形的处理(matlab tutorial, including the matlab software and the basic operation of data processing, graphics processing)

MATLAB學習文件大全，裡面包含許多使用及範例(MATLAB to study the document Guinness, which contains a lot of use and examples)

用MATLAB绘制分形蕨的GUI程序，是非线性科学中分形理论的经典例子(MATLAB fractal fern GUI process, the nonlinear fractal theory of the classic examples)

说明：  主要对扩展卡尔曼滤波（EKF）、无迹卡尔曼滤波（UKF）及改进无迹卡尔曼滤波（MAUKF）算法进行研究，研究了三种算法的基本原理和各自的特点。其中扩展卡尔曼滤波器是将卡尔曼滤波器局部线性化，其算法简单，计算量小，适用于弱非线性、高斯环境。无迹卡尔曼滤波器是用一系列确定样本来逼近状态的后验概率密度。改进无迹卡尔曼滤波算法在UKF的基础上引入衰减因子。(The thesis focuses on the extended Kalman filter (EKF), unscented Kalman filter (UKF) and the improvement of unscented Kalman filter (MAUKF) algorithm research, researched the basic principles of three algorithms and their characteristics. Extended Kalman filter (EKF) is the local linear Kalman filter, the algorithm and computation are simple in weakly nonlinear and Gaussian environment. Unscented Kalman filter (UKF) is determined using a series of samples to approximate the state posterior probability density. Improved UKF algorithm (MAUKF) is introduced attenuation factor based on the UKF.)

matlab linear phase FIR four type amplitude

matlab based single phase semi converter simulation model for power elecyronics study

说明：  根据张贤达版《现代信号处理》的SVD-TLS算法，基于奇异值分解的总体最小二乘法, SVD-TLS是一个在现代谱估计中一个基础的算法(SVD-TLS, Spectral estimation)

Locality Preserving Projections(LPP),局部保留投影，可以找出高维空间中的数据在低维空间中的投影，并保留了数据之间的相关性(Locality Preserving Projections (LPP), partial retention projection, you can find the data in high-dimensional space in a low dimensional space projection, and retains the correlation between data)

Extended Kalman Filter Tracking Object in 3-D(Assume that we want to track an object moving in 3-D space with constant velocity. Our instruments observe bearing, range and high(cylindrical coordinates). However, of an interest are rectangular coordinates. Since transformation is non-linear this requires use of extended Kalman filter. Because transformation is non-linear between X,Y and Range,Bearing and linear between Z and high(Z is height), this problems serves as a good comparason of how well extended Kalman filter can perform. By comparing its linear estimation error in Z to non-linear estimations in X and Y, we can judge how non-familiarities effect estimation. )

求解离散微分方程组的MATLAB 的原始方程以及程序(Original equations and procedures for solving the discrete differential equations MATLAB)