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I read in a pattern classification text, that if we consider weight vectors whose components are integer valued, the perceptron procedure would terminate in a finite number of steps.

What is the intuition and theory behind this?

EDIT: It is a homework problem from the text book Pattern classification by Duda, Hart, Stork, and I just wanted a hint, so posted the above query. Here is the actual homework problem:

Let ${y_{1},...,y_{n}}$ be a finite set of linearly separable samples in d dimensions. Suggest an exhaustive procedure that will find a separating vector in a finite number of steps. (You might wish to consider weight vectors whose components are integer valued.)

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