%%隐马尔科夫模型维特比实现。
clc;clear;
A = [0.5,0.25,0.25;0.375,0.125,0.375;0.125,0.675,0.375];%转换矩阵
[~,lA] = size(A);
B =[0.6,0.2,0.15,0.05;0.25,0.25,0.25,0.25;0.05,0.1,0.35,0.5];%混淆矩阵
pai = [0.63,0.17,0.2];%初始概率
out = [1,3,4,4,2,1,3,4,3,4,2];
yes_p = bsxfun(@times,pai',B(:,out(1)));
xulie =[];
for i = 2:1:length(out) %%out为输出序列
for j=1:lA %%
to_p = bsxfun(@times,yes_p(:,i-1),A(:,j));%%
[v,l] = max(to_p);%%
z(j) = l;%%
ye_p(j)=v*B(j,out(i));%%让最可能的天气状态乘以对应混淆概率
end
yes_p(:,i) = ye_p;
zh(:,i) = z';
end
[c,l] = max(yes_p(:,length(out)));
xulie(length(out)) = l;
for i =length(out):-1:2
xulie(i-1) = zh(l,i);
l = xulie(i-1);
%mid = zh(l,i);
%xulie(i-1) = mid;
%l = mid;
end
xulie%%输出序列
