Implementation of a Hidden Markov model on a feature Vector as well as calculating distance between two HMMs
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Hi,
Basically, a HMM is charecterized by the triplet (A,B,π).
I have read this paper * http://www.irisa.fr/vista/Papers/2007_icip_hervieu.pdf * and was trying to implement Hidden Markov model on my feature vector.
I have my Feature vector(row vector) as V = [V1 V2 V3 V4....Vn]. I want to do the following:
1) I want to distribute the values in the V,on an interval containing a given percentage P,within a domain [-S,S] (which is divided into N number of bins).
2) Let us assume that the no. of states are M.I want to calculate the A, π and B matrices using a least square technique.
3) Once,we calculate the parameters A, π and B for Feature vector 1 as well as Feature vector 2, I want to calculate the distance,inorder to compare two HMMs,proposed by Ranber.
I would be really glad,if someone can help me with the code. Thanks in advance.
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