EEMD

hybrid power train simulation

此系统为伺服系统的三环PID控制的MATLAB仿真代码(This system is a three-ring servo system PID control of MATLAB simulation codes)

resolution de l equation NLSE avec l efet de Raman

Matlab7.0-Simulink6.0应用实例仿真与高效算法开发书中程序代码。我找了好久才找到。希望对搞控制的朋友有帮助。(Matlab7.0-Simulink6.0 application examples and efficient algorithm simulation code developed in the book. I am looking for a long time to find. I hope to help a friend out control.)

TQWT工具箱，可调Q因子小波变换，可用于轴承齿轮故障诊断。(TQWT toolbox, adjustable Q factor wavelet transform, can be used for bearing gear fault diagnosis.)

Matlab的Optimization软件包，虽然能很好地解决线性规划问题，但对于无解和有无穷个解地情况，结果不能让人满意，本人编了几个函数用于打印单纯形表。(Matlab Optimization package, Although able to solve linear programming problems, but no solution and a solution to the endless, the results are not satisfying. I compiled several functions for printing simplex table.)

Matlab implementation of the Kernel Density estimation for 2D array/matrix

EKF,PF,MVEKPF仿真算法，关于这几种卡尔曼滤波算法、粒子滤波算法的仿真对比分析。(The simulation algorithm of EKF,PF,MVEKPF。 About the several kalman filtering algorithm, particle filter algorithm simulation analysis. )

智能视觉监控利用计算机视觉技术在不需要人为干预的情况下,通过对摄像 头拍摄的图像序列的自动分析实现对被监控场景中的运动目标检测、识别和跟踪, 并在此基础上分析和判断目标的行为,涉及到网络通信、图像处理、数据压缩、 人工智能等多项技术 (Intelligent visual surveillance using computer vision technology in without the need of human intervention, the camera 头拍摄的图像序列的自动分析实现对被监控场景中的运动目标检测、识别和跟踪,并在此基础上分析和判断目标的行为,涉及到网络通信、图像处理、数据压缩、 Automatic image analysis of sequence header shot of the moving target detection, recognition and tracking in the scene to be monitored, and based on the analysis and judge the behavior of the objects, relates to the network communication, image processing, data compression, 人工智能等多项技术 Artificial intelligence technology )

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.)