文件名称:kalmantracking
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 14kb
- 下载次数：
- 0次
- 提 供 者：
- im***
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
本文件用matlab 语言，对kalman滤波的方法进行仿真，画出来原始曲线，观察值，和跟踪曲线，会对初学者有很大的帮助！-this document using Matlab language, Kalman filtering method simulation, sketching out the original curve, observed values, and tracking curve, beginners will be of great help!
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(系统自动生成,下载前可以参看下载内容)
下载文件列表
kalman tracking
...............\Kalman_matlab
...............\.............\AR_to_SS.m
...............\.............\block.m
...............\.............\convert_to_lagged_form.m
...............\.............\em_converged.m
...............\.............\ensure_AR.m
...............\.............\eval_AR_perf.m
...............\.............\gauss.m
...............\.............\gaussian_prob.m
...............\.............\gaussplot.m
...............\.............\gsamp.m
...............\.............\kalman_filter.m
...............\.............\kalman_smoother.m
...............\.............\kalman_update.m
...............\.............\learning_demo.m
...............\.............\learn_AR.m
...............\.............\learn_AR_diagonal.m
...............\.............\learn_kalman.m
...............\.............\normal_coef.m
...............\.............\rand_psd.m
...............\.............\README
...............\.............\sample_lds.m
...............\.............\smooth_update.m
...............\.............\SS_to_AR.m
...............\.............\tracking_demo.m
...............\Kalman_matlab
...............\.............\AR_to_SS.m
...............\.............\block.m
...............\.............\convert_to_lagged_form.m
...............\.............\em_converged.m
...............\.............\ensure_AR.m
...............\.............\eval_AR_perf.m
...............\.............\gauss.m
...............\.............\gaussian_prob.m
...............\.............\gaussplot.m
...............\.............\gsamp.m
...............\.............\kalman_filter.m
...............\.............\kalman_smoother.m
...............\.............\kalman_update.m
...............\.............\learning_demo.m
...............\.............\learn_AR.m
...............\.............\learn_AR_diagonal.m
...............\.............\learn_kalman.m
...............\.............\normal_coef.m
...............\.............\rand_psd.m
...............\.............\README
...............\.............\sample_lds.m
...............\.............\smooth_update.m
...............\.............\SS_to_AR.m
...............\.............\tracking_demo.m