sample_markov_chain.m

隐马尔科夫模型对文本信息进行抽取利用MATLAB实现

function state = sample_markov_chain(initial_prob, trans, len, numex)
%
% Generate random sequences from a Markov chain.
% state = sample_markov_chain(initial_prob, trans, len, numex)
%
% Each row of state is a sequence of length len.
% The number of rows, numex, is 1 if omitted.

if nargin==3
  numex = 1;
end

state = zeros(numex,len);
S = length(initial_prob); % num states

R = rand(len*numex,1);
rcount = 1;


% Compute all the cdf's ahead of time

init_cumprob = zeros(1,S+1);
init_cumprob(1) = 0;
for j=1:S
  init_cumprob(j+1) = init_cumprob(j) + initial_prob(j);
end

cumprob = zeros(S, S+1);
for i=1:S
  cumprob(i,:) = [0 cumsum(trans(i,:))];
end


for ex=1:numex
  t = 1;
  
  % j = sample(init_cumprob, R, rcount);
  r = R(rcount);
  rcount = rcount + 1;
  for j=1:S
    if (r >= init_cumprob(j)) & (r < init_cumprob(j+1))
      break;
    end
  end
  
  state(ex,t) = j;
end


  
for ex=1:numex
  for t=2:len
    i = state(ex,t-1);

    % j = sample(cumprob(i,:), R, rcount);
    r = R(rcount);
    rcount = rcount + 1;
    for j=1:S
      if (r >= cumprob(i,j)) & (r < cumprob(i,j+1))
	break;
      end
    end
    
    state(ex,t) = j;
  end
end