kalman-1

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.)

simulink model simulating a microwave oven

the main program for standard leach

关于小波去噪 适合初学者的一个小程序 希望对大家有帮助(on wavelet denoising for beginners of a small program you want to help! !)

digital to analog converter

Friction parameters identification

说明：  移动通信中关于瑞丽信道衰弱的MATLAB仿真程序。(Rui Lixin Road Mobile Communications weak on MATLAB simulation program.)

The purpose of this paper is to provide a practical introduction to the discrete Kalman filter. This introduction includes a description and some discussion of the basic discrete Kalman filter, a derivation, description and some discussion of the extended Kalman filter, and a relatively simple (tangible) example with real numbers & results.(The purpose of this paper is to provide a pra ctical introduction to the discrete Kalman fil ter. This introduction includes a description and some discussion of the basic discrete Kalma n filter, a derivation. description and some discussion of the extende d Kalman filter. and a relatively simple (tangible) example wit h real numbers)

基于混沌单纯形法算子的布谷鸟搜索算法，算法引入混沌算子及单纯形法，提高了布谷鸟搜索算法的寻优能力。(an improved cuckoo search algorithm (CS) using chaotic local search and simplex method (CLSCS) )

详细的介绍了maple和matlab科学计算的问题也原理(Detailed description of the maple and matlab scientific computing problem principle)