wikipedia上有個java版的Viterbi(維特比)實(shí)現(xiàn)程序（
http://en.wikipedia.org/wiki/Viterbi_algorithm），但是3個觀察序列會標(biāo)注出4個狀態(tài)序列。
下面本人寫的這個Viterbi(維特比)實(shí)現(xiàn)程序就沒這個問題，3個觀察序列就只標(biāo)注出3個狀態(tài)序列。
public class Viterbi
{
public static void main(String[] args)
{
String[] states = {"Rainy", "Sunny"};
String[] observations = {"walk", "shop", "clean"};
double[] start_probability = {0.6, 0.4};
double[][] transition_probability = {{0.7, 0.3}, {0.4, 0.6}};
double[][] emission_probability = {{0.1, 0.4, 0.5}, {0.6, 0.3, 0.1}};
forward_viterbi(observations,states,start_probability,transition_probability,emission_probability);
}
public static void forward_viterbi(String[] observations, String[] states,double[] start_probability, double[][] transition_probability, double[][] emission_probability)
{
int[][] path=new int[observations.length][states.length];
double[][] r=new double[observations.length][states.length];
for(int j=0;j<states.length;j++)
{
r[0][j]=start_probability[j]*emission_probability[j][0];
path[0][j]=0;
}
for(int t=1;t<observations.length;t++)
{
for(int i=0;i<states.length;i++)
{
double tmp=0;int m=0;
for(int j=0;j<states.length;j++)
{
double tem=r[t-1][j]*transition_probability[j][i]*emission_probability[i][t];
if(tem>tmp)
{
tmp=tem;
m=j;
}
}
r[t][i]=tmp;
path[t][i]=m;
}
}
double p=0;int m=0;
for(int i=0;i<r[0].length;i++)
{
if(r[r.length-1][i]>p)
{
p=r[r.length-1][i];
m=i;
}
}
System.out.println("p="+p);
int[] trace=new int[observations.length];
trace[observations.length-1]=m;
for(int t=observations.length-1;t>0;t--)
{
trace[t-1]=path[t][m];
m=path[t][m];
}
for(int i=0;i<trace.length;i++)
System.out.println(states[trace[i]]);
}
}。
posted on 2012-09-07 16:43
nianzai 閱讀(1987)
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