Take the 2-minute tour ×
Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It's 100% free, no registration required.

I am using VOMC in order to implement a real-time system. The Loop of the system is the following: LOOP{

1)Get Input and Train VOMC according to it 2)Get output from Markov Chain

} With the above description I am want to show that in every iteration my Markov chain should be altered, at least the values of some transitions.

If for example I had a transition of A->B with probability of .6 and A->C with 0.4. This would mean that 6 out of 10 times I would choose A->B and 4 out of 10 A->C.

First question how do I determine the order of such occurrences? Randomly?

Second Question, if that chain is modified on every it iteration which means that I can have: fx ITERATION_2: A->B 0.5, A->C 0.5 ITERATION_3: A->B 0.33, A->C 0.66

How can I solve such a system?

Any Theoretical or Practical information would be very much appreciated!

PS I am aware of some concepts of Markov Chains but as you can see I lack of the theoretical background in solving.

share|improve this question
add comment

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Browse other questions tagged or ask your own question.