Airdryer

test car lane changing with matlab simulink based on fuzzy control test 4.

This project is based on group human activity classification using matlab

针对电机的直接转矩控制，通过MATLAB的simulink进行了详细的仿真，并且给出了一篇仿真的论文。(For direct torque control of the motor , through the MATLAB simulink carried out a detailed simulation , and gives a simulation papers. )

永磁直驱风电机组机侧变流器控制simulink仿真(Permanent magnet direct drive wind turbine machine side converter control simulink simulation)

俄罗斯方块的MATLAB版，其中附源代码。(The MATLAB version of Tetris, including the source code attached.)

dpxm simulink仿真 模块建立 波形分析(dpxm Simulink simulation)

各种算法实例、算法讲解及代码，给代码在matlab2008验证过(Examples of various algorithms, algorithms and code to explain to the code matlab2008 verified)

The early detection of arrhythmia is very important for the cardiac patients. This is done by analyzing the electrocardiogram (ECG) signals and extracting some features from them. These features can be used in the classification of different types of arrhythmias. In this paper, we present three different algorithms of features extraction: Fourier transform (FFT), Autoregressive modeling (AR), and Principal Component Analysis (PCA). The used classifier will be Artificial Neural Networks (ANN). We observed that the system that depends on the PCA features give the highest accuracy. The proposed techniques deal with the whole 3 second intervals of the training and testing data. We reached the accuracy of 92.7083 compared to 84.4 for the reference that work on a similar data.

遗传算法工具箱，谢菲尔德大学，MATLAB源码(Genetic algorithm toolbox, University of Sheffield, MATLAB source code)

Particle filtering is an non-parameterized algorithm via sequential Monte Carlo simulation to actualize bayesian estimation. This paper expatiated the development and the research status of particle filtering at present.Then,introduces and analyses the principle of particle filtering、the existed key problems and countermeasures in detail.Furthermore,it sum up eleven improved methods of particle filtering algorithm.Meanwhile,applications are addressed in this paper.Finally ,the prospect of particle filtering is presented.