Page 90 - Algorithm Collections for Digital Signal Processing Applications using MATLAB
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78 Chapter 2
Figure 2-2. Illustration of K-Means Algorithm
Figure 2-3. Data along with the final centroids obtained by k-means algorithm
In the above-mentioned example, the data ranges from 0.0067 to 0.9925
and the six centroids obtained in the 10 th iteration are displayed below.
0.0743 0.2401 0.4364 0.6115 0.7763 0.9603 (see the Figure 2-3).
3.3 Matlab Program for the K-means Algorithm
Applied for the Example given in Section 3.2
kmeansgv.m
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a=rand(1,100);
plot(a,zeros(1,100),'*');
b=rand(1,6);
for iter=1:1:10
hold off
M=[(a-b(1)).^2;(a-b(2)).^2;(a-b(3)).^2;(a-b(4)).^2;(a-b(5)).^2;(a-b(6)).^2;];
[P,CLUSTERNO]=min(M);
u=['r','g','b','c','m','y'];
figure
