For example, you might read 1024 samples at 1 MHz. Just to review, a typical system that uses a Fourier transform will read a number of samples at some clock frequency using an analog to digital converter. The math is much easier and you can usually implement it faster and smaller than a full transform, even on small CPUs. It is essentially a fast Fourier transform algorithm stripped down to compute just one frequency band of interest. But if you go that route you are going to do a lot of math to compute things you don’t care about just so you can pick out the one or two pieces you do care about. You don’t care about anything else.Ī Fourier transform can do either of those jobs. If you are decoding TouchTones, you only need to know if two of eight frequencies are present. You only need to know if one frequency is present or if it isn’t. However, sometimes it is more than you need.įor example, consider tuning a guitar string. If you need to understand the entire frequency spectrum of a signal or you want to filter portions of the signal, this is definitely the tool for the job. In particular, for computers, we don’t really have a nice equation so we use the discrete version of the transform which takes a series of measurements at regular intervals. You probably have at least a nodding familiarity with the Fourier transform, a mathematical process for transforming a time-domain signal into a frequency domain signal.
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