kmean

matlab code for modelling low pass filters

电源控制环路设计英文课件电源控制环路设计英文课件

Check this file for sensor

数学建模1998年B题，有关灾情巡视的Matlab程序，是图论方面的问题(B 1998, issue of mathematical modeling, the disaster visited the Matlab program, is graph theory problems)

基于卡尔曼的视频序列帧图像的跟踪程序，还有condense算子法的跟踪，可动态读取序列帧并对其进行估计跟踪，非常好的程序。(based video sequence pictures of the tracking process, in addition to condense operator law tracking, Dynamic sequences can be read on its frame and estimated tracking, very good procedures.)

Electronic design dew sensor

介绍matlab的gui设计工具gaide的使用方法,很有用(introduced Matlab gui gaide design tools to use and useful)

Another particle filter implementation (by by Diego Andrés Alvarez Marín) that implements Arulampalam et. al. (2002). A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing. 50 (2). p 174--188

卷积编码和解码器，通俗易懂，误码率低，有BER仿真曲线(Convolutional encoding and decoding, and user-friendly, error rate and low BER simulation curves)

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.)