For the given perceptron network, observe that the intial assignment of weights is completely random.

Observe the number of iterations required for the weights to converge, i.e. to achieve classification for the given case.

Repeat the experiment for different number of samples per class and observe if there exists a relation between the number of samples per class and iteration steps required to converge .