First let me show this picture of my HMM Model.

enter image description here

Experimentally I get the High and Low values, whereas the states {|-1>, |0>, |1>} are unknown. Although I know that when I measure High signal I have |-1>. Also transition from |-1> to |1> are forbidden.

I heard that using a Markov Model here might be good to analyze a given time trace and get information about the hidden states. If I understand the Idea correctly the HMM gives me the most likely time trace given some transition probabilities. Then I optimize this time trace regarding my missing transition parameters ?

I'm glad for any help you can provide me. Also for good resources on how to implement Baum-Welch or Viterbi.

Okay thanks for the comment.

My question is:

What is the best and most time efficient way to get the transition rates between the hidden states ?

  • $\begingroup$ This is a good description of your situation / problem. Can you clarify what your question is exactly? $\endgroup$ – gung - Reinstate Monica Jan 26 '17 at 13:56

here you go- [link] https://www.inf.ed.ac.uk/teaching/courses/asr/2012-13/asr03-hmmgmm-4up.pdf

I have understood HMM from these 3 videos- [link] https://www.youtube.com/watch?v=E3qrns5f3Fw
[link] https://www.youtube.com/watch?v=cjlhpaDXihE
[link] https://www.youtube.com/watch?v=5sGEF-e82yY

transition probabilities would be calculated in training phase.[Forward-backward Algo]

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