hidden-markov-models

I'm trying to build the transition matrix for a Markov Chain in MATLAB; I have several different observation sequences (all of varying lengths) and I need to generate the transition matrix using those. Constructing a multi-order Markov chain transition matrix in Matlab shows me how to build a transition matrix with a single observation sequence. How can I construct one using observations of different length? One example can be that one sequence is 1,2,3,4 and another is 4,5,6. Is there any way to do this without having to for loop through all sequences and computing counts? So for Markov

I am having a tough time in figuring out how to use Kevin Murphy's HMM toolbox Toolbox . It would be a great help if anyone who has an experience with it could clarify some conceptual questions. I have somehow understood the theory behind HMM but it's confusing how to actually implement it and mention all the parameter setting. There are 2 classes so we need 2 HMMs. Let say the training vectors are :class1 O1={ 4 3 5 1 2} and class O_2={ 1 4 3 2 4}. Now,the system has to classify an unknown sequence O3={1 3 2 4 4} as either class1 or class2. What is going to go in obsmat0 and obsmat1? How to