EM algorithm with a Rauch-Tung-Striebel Smoother and an M step,内有说明
标签： Rauch-Tung-Striebel algorithm Smoother with
上传时间： 2014-01-06
上传用户：mhp0114
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel Smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
标签： Rauch-Tung-Striebel algorithm Smoother which
上传时间： 2016-04-15
上传用户：zhenyushaw
comparison of Extended Switching Kalman Filter and Smoother
标签： comparison Switching Extended Smoother
上传时间： 2013-12-27
上传用户：waizhang
Matlab工具包补充算发，包括各种噪声代码及滤波倒向Smoother代码等
上传时间： 2013-12-19
上传用户：佳期如梦
documentation for optimal filtering toolbox for mathematical software package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter and unscented Kalman filter for discrete time state space models. Also included in the toolbox are the Rauch-Tung-Striebel and Forward-Backward Smoother counter-parts for each filter, which can be used to smooth the previous state estimates, after obtaining new measurements. The usage and function of each method are illustrated with five demonstrations problems. 1
标签： documentation mathematical for filtering
上传时间： 2014-01-20
上传用户：changeboy
documentation for optimal filtering toolbox for mathematical software package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter and unscented Kalman filter for discrete time state space models. Also included in the toolbox are the Rauch-Tung-Striebel and Forward-Backward Smoother counter-parts for each filter, which can be used to smooth the previous state estimates, after obtaining new measurements. The usage and function of each method are illustrated with five demonstrations problems. 1
标签： documentation mathematical for filtering
上传时间： 2013-12-10
上传用户：zxc23456789
