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HHM
Hidden Markov Model (HMM) Toolbox for Matlab
The new version computes the summed two-slice marginals, to save space (suggestion of Herbert Jaeger).
This toolbox supports inference and learning for HMMs with discrete outputs (dhmm's), Gaussian outputs (ghmm's), or mixtures of Gaussians output (mhmm's). The Gaussians can be full, diagonal, or spherical (isotropic). It also supports discrete inputs, as in a POMDP. The inference routines support filtering, smoothing, and fixed-lag smoothing. For more general models, please see my Bayes Net Toolbox.
Written by Steinar Thorvaldsen, 2004. Last updated: Jan. 2006.Dept. of Mathematics and Statistics
University of Tromsø - Norway.
steinart@math.uit.no
MendelHMM is a Hidden Markov Model (HMM) tutorial toolbox for Matlab. These pages describe the graphical user interface (GUI) and the main operations of the program. The toolbox is free for academic use. Ref.: S. Thorvaldsen: A tutorial on Markov models based on Mendel's classical experiments. Journal of Bioinformatics and Computational Biology, Vol. 3, No. 6 (2005), 1441-1460.
To run the program you should make the following steps:
Download the program to your local PC and install (unzip) it in a directory like …\mendel2. Run Matlab v. 6.5 or later 3. Set working directory to ...\mendel (root directory of the toolbox) 4. Type "mendelHMM"
Mendel HMM Toolbox for Matlab
When you type "mendelHMM" in Matlab command window the main window of GUI will appear. In left part of main window there is a frame containing controls for loading and managing training data. On right there is a frame containing controls for managing the Hidden Markov model. Button " >Estimate (EM)>" runs estimation of model from the selected training set. Baum Welch algorithm is used starting from the pre-selected number of states and initialization method, but any other values of hidden parameters are ignored. Button "
Main window of the program. There are buttons for loading models and training sets, viewing individual sequences and results.
In his historic experiment, Gregor Mendel (1822-1884) examined 7 simple traits in the common garden pea (Pisum). A trait (called phenotype) is one which occurs either in one variation or another, with no in-between. These plants are naturally self-pollinating and exhibited traits which occur in very distinct forms:
Experiment number
Sample size N in F2-generation
Dominant expression
Recessive expression
مقاله درمورد HHM