Kalman_matlab
所属分类：matlab编程
开发工具：matlab
文件大小：179KB
下载次数：10
上传日期：2016-02-17 15:02:30
上 传 者：
韩闯
说明： 使用卡尔曼滤波器实现单目标的跟踪，完整的matlab程序，调用的工具包很简单，有下载网址，里面包含使用说明，效果非常不错。
(Using kalman filter to realize single target tracking, complete the matlab program, called toolkit is very simple, have download site, it contains the instructions, the effect is very good.)
文件列表:
Kalman_matlab\AR_to_SS.m (1107, 2003-05-28)
Kalman_matlab\convert_to_lagged_form.m (425, 2003-05-28)
Kalman_matlab\ensure_AR.m (354, 2003-05-28)
Kalman_matlab\eval_AR_perf.m (1045, 2003-05-28)
Kalman_matlab\gaussian_prob.m (733, 2003-05-28)
Kalman_matlab\kalman_filter.m (2899, 2003-05-28)
Kalman_matlab\kalman_forward_backward.m (2392, 2003-05-28)
Kalman_matlab\kalman_smoother.m (1584, 2003-05-28)
Kalman_matlab\kalman_update.m (1840, 2003-05-28)
Kalman_matlab\learning_demo.m (1022, 2003-05-28)
Kalman_matlab\learn_AR.m (819, 2003-05-28)
Kalman_matlab\learn_AR_diagonal.m (687, 2003-05-28)
Kalman_matlab\learn_kalman.m (5498, 2003-05-28)
Kalman_matlab\plotgauss2d.m (898, 2003-05-28)
Kalman_matlab\plot_ellipse.m (507, 2003-05-28)
Kalman_matlab\sample_gaussian.m (505, 2007-01-10)
Kalman_matlab\sample_lds.m (1797, 2003-05-28)
Kalman_matlab\smooth_update.m (1199, 2003-05-28)
Kalman_matlab\SS_to_AR.m (579, 2003-05-28)
Kalman_matlab\tracking_demo.asv (1989, 2012-06-18)
Kalman_matlab\tracking_demo.m (1989, 2012-06-18)
Kalman_matlab\ͼ1.fig (29025, 2016-02-17)
Kalman_matlab\ͼ1.jpg (23783, 2016-02-17)
Kalman_matlab\ͼ2.fig (92800, 2016-02-17)
Kalman_matlab\ͼ2.jpg (22500, 2016-02-17)
Kalman_matlab\新建 Microsoft Word 文档.docx (14652, 2016-02-17)
Kalman_matlab (0, 2016-02-17)
Kalman filter toolbox written by Kevin Murphy, 19***.
See http://www.ai.mit.edu/~murphyk/Software/kalman.html for details.
This version was last updated on 18 January 2003.
Installation
------------
1. Install KPMtools from http://www.ai.mit.edu/~murphyk/Software/KPMtools.html
3. Assuming you installed all these files in your matlab directory, In Matlab type
addpath matlab/KPMtools
addpath matlab/Kalman
Demos
-----
See tracking_demo.m for a demo of 2D tracking.
See learning_demo.m for a demo of parameter estimation using EM.
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