kaerman

matlab tutorial and explication

基于高斯过程的约束谱聚类，lu zhengdong的论文cvpr08的实现代码，算法可以直接运行，其中含有两个demo(constrained spectral clustering through affinity propogation)

Matlab基础及其应用教程，适用于初学者快速入门。(Matlab and its application tutorial for beginners to get started.)

用MATLAB/Sinulink 搭建的SVPWM空间矢量控制程序(MATLAB/Sinulink structures of SVPWM space vector control program)

将txt中的数据导入matlab中并形成x1,y1,x2,y2...，的变量名，方便管理和调用(Read data in txt file into matlab and generate variables like x1,y1,x2,y2 and so on. Manage the variables for convenience)

均匀线性阵列的波束成形.波束成形入门级代码(Beamforming uniform linear array)

h infinity controller code

particle swarm optimization

对于随机数据和Iris数据的层次聚类算法(For random data and Iris data hierarchical clustering algorithm)

GM_PHD_Filter Version 1.09, 13th December 2013 Matlab code by Bryan Clarke b.clarke@acfr.usyd.edu.au with: - some Kalman filter update code by Tim Bailey, taken from his website http://www-personal.acfr.usyd.edu.au/tbailey/software/ - error_ellipse by AJ Johnson, taken from Matlab Central http://www.mathworks.com.au/matlabcentral/fileexchange/4705-errorellipse Algorithm by Ba-Ngu Vo & Wing-Kin Ma in: B.-N. Vo, W.-K. Ma, "The Gaussian Mixture Probability Hypothesis Density Filter", IEEE Transactions on Signal Processing, Vol 54, No. 11, November 2006, pp4091-4104 This is an implementation of a gaussian mixture probability hypothesis density filter (GM-PHD) for a simulated tracking problem. The problem specification is given in the above paper - in summary, two targets move through the environment, there is a lot of clutter on the measurement, and about halfway through a third target spawns off one of the two targets.(GM_PHD_Filter Version 1.09, 13th December 2013 Matlab code by Bryan Clarke b.clarke@acfr.usyd.edu.au with: - some Kalman filter update code by Tim Bailey, taken from his website http://www-personal.acfr.usyd.edu.au/tbailey/software/ - error_ellipse by AJ Johnson, taken from Matlab Central http://www.mathworks.com.au/matlabcentral/fileexchange/4705-errorellipse Algorithm by Ba-Ngu Vo & Wing-Kin Ma in: B.-N. Vo, W.-K. Ma, "The Gaussian Mixture Probability Hypothesis Density Filter", IEEE Transactions on Signal Processing, Vol 54, No. 11, November 2006, pp4091-4104 This is an implementation of a gaussian mixture probability hypothesis density filter (GM-PHD) for a simulated tracking problem. The problem specification is given in the above paper- in summary, two targets move through the environment, there is a lot of clutter on the measurement, and about halfway through a third target spawns off one of the two targets.)