What Is Discretization?
Discretization is the process of reducing a continuum to a finite set of points. It's like when your mom used to cut up your meat for you into bite-sized pieces—except instead of eating it, we're talking about continuous signals. It's also like when someone takes something real and makes it into a cartoon. It is integral to analog-to-digital conversion. Analog-to-digital conversion (ADC) converts an analog signal into a digital one. This happens in digital computing, such as with audio or video signals. It relates to quantization, which refers to converting an analog value into its digital representation by choosing its nearest integer value from an infinite set of possible discrete values. If you've ever tried to find the derivative of a function, you know how hard it can be. It is not only a matter of finding the root of the equation but also one of evaluating continuity and infinitesimals. Aristotle was the first to describe this problem and did so in his usual colorful way: "There can't be any infinity of continuous magnitudes." In other words, you could never get there if you had infinite small steps between two points. Yet, that's precisely what we try to do when calculating derivatives—we take infinitely small steps between two points to find their slope Discretization and quantization are like two sides of the same coin. They both break things down into manageable parts. Discretization is dividing a continuous function into smaller, discrete pieces. This is necessary to digitize something that would be too complicated to represent with a single number on the computer. Quantization assigns values to those discrete pieces so you can use them in your program. Quantization is where you trade precision (the amount of detail) and range (the number of possible values). Suppose you have an exact value with an extensive range. In that case, more information is available in your data set than if you had less-precise values covering smaller ranges—so choosing how much precision and content to include in your algorithm can be tricky!
Related Terms by Computing
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