www.pudn.com > hmm--matlab.rar > inithmm.asv

function hmm = inithmm(samples,M) 
 
K = length(samples); %语音样本数 
N = length(M);  %状态数 
hmm.N = N; 
hmm.M = M; 
 
%初始概率矩阵 
hmm.init = zeros(N,1); 
hmm.init(1) = 1; 
 
%转移概率矩阵 
hmm.trans = zeros(N,N); 
for i = 1:N-1 
    hmm.trans(i,i) = 0.5; 
    hmm.trans(i,i+1) = 0.5; 
end 
hmm.trans(N,N) = 1; 
 
%概率密度函数的初始聚类 
%平均分段 
for k = 1:K 
    T = size(samples{k},1); 
    samples{k}.segment = floor([1:T/N:T T+1]); 
end 
 
%对属于每个状态的向量进行K均值聚类，得到连续混合正态分布 
for i = 1:N 
    %吧相同聚类和相同状态的向量组合到一个向量里 
    vector = []; 
    for k =1:K 
        seg1 = samples{k}.segment(i); 
        seg2 = samples{k}.segment(i+1)-1; 
        vector = [vector;samples{k}(seg1:seg2,:)]; 
    end 
    mix(i) = getmix(vector,M(i)); 
end 
 
hmm.mix = mix; 
 
function mix = getmix(vector,M) 
[mean esq nn] = kmeans(vector,M); 
 
%计算每个聚类的标准差，对角阵，只保存对角线上的元素 
for j = 1:M 
    ind = find(j==nn); 
    tmp = vector(ind,:); 
    var(j,:) = std(tmp); 
end 
 
%计算每个聚类中的元素数，归一化为各个pdf的权重 
weight = zeros(M,1); 
for j = 1:M 
    weight(j) = sum(find(j==nn)); 
end 
weight = weight/sum(weight); 
 
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