Page 85 - Algorithm Collections for Digital Signal Processing Applications using MATLAB

2. Probability and Random Process 73

2.3 Matlab Program

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gmmmodelgv.m

%GMM MODEL
cluster1=clustercol([0.9 0.8],100);
cluster2=clustercol([0.7 0.6],100);
cluster3=clustercol([0.5 0.4],150);
clustertot=[cluster1 cluster2 cluster3];
%[p,q]=kmeans(clustertot',3);This may be used for initializing the means
q(1,:)=[0.83 0.79];
q(2,:)=[0.76 0.74];
q(3,:)=[0.6 0.3];

%To Estimate q ,cov1,cov2,cov3
[p]=clusterno(clustertot,q);
[m1,n1]=find(p==1);
collect1=clustertot(:,n1);
if(length(n1)~=0)
cov1=cov(collect1');
else
cov1=diag([1 1]);
end
[m1,n1]=find(p==2);
collect2=clustertot(:,n1);
cov2=cov(collect2');
if(length(n1)~=0)
cov2=cov(collect2');
else
cov2=diag([1 1]);
end
[m1,n1]=find(p==3);
collect3=clustertot(:,n1);
cov3=cov(collect3');
if(length(n1)~=0)
cov3=cov(collect3');
else
cov3=diag([1 1]);
end
plot(collect1(1,:),collect1(2,:),'r*')