Otherwise it simply requires to much power to process it. It is often used in computer science to reduce the quantity of information compared to the original signal. It is very easy and accurate to transform a continuous signal into a non continuous signal. Typical example of some continuous/discrete signals: If you take two pixels side by side, one can be white while the other is black. In the real world, signals are often "continuous." If you take two points A and B and A is very close to B then F(A) is very close to F(B). First, let's explain aliasing and why people are so keen on removing it with anti-aliasing.
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