matlab

基于卡尔曼滤波技术的永磁同步电机故障诊断与容错控制源码，文章已经发表了，收录于ICACMVE‘07会议论文(Kalman filtering technique based on permanent magnet synchronous motor fault diagnosis and fault-tolerant control source, the article has published a collection of conference papers in ICACMVE)

LADT ECG Compression Algorithm 2

simple fuzzy rule base

2fsk和matlab程序 对2fsk进行M语言编译码，实现功能(2fsk and matlab yingyong matlab jinxing fangzhen)

k-means分类测试，通过自己建造数据集测试分类方法使用效果(K- means classification test, by building their test data set classification method using effect)

给出了直流电机双闭环调速系统在Matlab/simulink 下的仿真程序，是电气工程及其自动化专业毕业设计中 所能用到得MATLAB仿真。(Gives the two-loop DC motor speed control system in Matlab/simulink simulation under the procedures, graduate electrical engineering and automation design can be used in MATLAB simulation.)

基于分形理论与WZ模型的针板电极系统击穿时电树枝物理现象的计算机模拟(Simulation of electrial breakdown treeing in a needle-plate configuration based on fractal theory and WZ model.)

用K均值算法和C模糊算法对sonar数据和iris数据进行分类。 K均值算法是一种很常用的聚类算法，其基本思想是，通过迭代寻找K个聚类的一种划分方法，使得用这K个聚类的均值来代表各类样本是所得到的的总体误差最小。 模糊C均值（FCM）算法在K均值算法的基础上，用模糊子集代替确定子集，从而得到模糊的分类结果，即分类结果的模糊化。(Sonar data and iris data are classified by means of K mean algorithm and C fuzzy algorithm. The K mean algorithm is a very common clustering algorithm. Its basic idea is to find a partition method of K clustering by iteration, so that the average error of the mean of the K clustering is minimized. The fuzzy C mean (FCM) algorithm is based on the K mean algorithm. The fuzzy subset is replaced by the fuzzy subset, thus the fuzzy classification result is obtained, that is, the classification result is fuzzed.)

说明：  流场的本征正交分解，降阶，数据分析，提取流场中的主要流动结构(Proper Orthogonal Decomposition)

时频分析工具包，可用于非平稳信号处理，for matlab(This is the Time-Frequency Toolbox, a collection of about 100 M-files , developed for the analysis of non-stationary signals using time-frequency distributions. It consists in groups of signal generation files, processing files and post-processing files (including visualization tools). The toolbox contains numerous algorithms for time-frequency signal analysis, with special emphasis on quadratic energy distributions within Cohen s class and the affine class, including most recent developments based on reassignment. The Time-Frequency Toolbox has been developed by Francois Auger, Olivier Lemoine, Paulo Gonlv and Patrick Flandrin during the years 1995-1996. Later, modifications for Matlab 5 were made available.)