camir-aes2014: toolboxes/FullBNT-1.0.7/HMM/mc_sample

first hg version after svn

rev	line source
wolffd@0	1 function S = sample_mc_endstate(startprob, trans, endprob)
wolffd@0	2 % SAMPLE_MC_ENDSTATE Generate a random sequence from a Markov chain until enter the endstate.
wolffd@0	3 % seq = sample_mc(startprob, trans, endprob)
wolffd@0	4
wolffd@0	5 % add an end state
wolffd@0	6 Q = size(trans,1);
wolffd@0	7 transprob = zeros(Q,Q+1);
wolffd@0	8 end_state = Q+1;
wolffd@0	9 for i=1:Q
wolffd@0	10 for j=1:Q
wolffd@0	11 transprob(i,j) = (1-endprob(i)) * trans(i,j);
wolffd@0	12 end
wolffd@0	13 transprob(i,end_state) = endprob(i);
wolffd@0	14 %assert(approxeq(sum(transprob(i,:)), 1))
wolffd@0	15 end
wolffd@0	16
wolffd@0	17 S = [];
wolffd@0	18 S(1) = sample_discrete(startprob);
wolffd@0	19 t = 1;
wolffd@0	20 p = endprob(S(t));
wolffd@0	21 stop = (S(1) == end_state);
wolffd@0	22 while ~stop
wolffd@0	23 S(t+1) = sample_discrete(transprob(S(t),:));
wolffd@0	24 stop = (S(t+1) == end_state);
wolffd@0	25 t = t + 1;
wolffd@0	26 end
wolffd@0	27 S = S(1:end-1); % don't include end state

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