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Imagine you have a voice recording. You are looking at it a long squiggly line with no uniformity. Zoom way in. If you go far enough it’ll just look like a cur
by SV_BubbleTime 4y ago
Imagine you have a voice recording. You are looking at it a long squiggly line with no uniformity.
Zoom way in. If you go far enough it’ll just look like a curved line.
That curved line can be estimated down into a sin wave, or more accurately, a few sin waves that combine to make almost the same wave you have.
FFT is a way to take a complex wave and reduce it down to the sin wave components that would all combine to make it up.
To practically apply this, your voice recording is very high resolution and has a lot of bits at a high sample rate. If you instead used sin waves to represent the data, it could be almost as good sounding while being a lot less data to store.
… Watch a video. It’s something many people need to see to get.
- AwaAwa 4y agoGreat explanation! I'm finally on the first step of understanding. Now to read more!
- jaypinho 4y agoI once read an explanation of the Fourier transformation as akin to looking at a fully blended smoothie and being able to calculate exactly how much of each ingredient went into it. I don't profess to be a DSP expert whatsoever, but the more familiar I've become with Fourier transformations, the more apt that analogy seems. Once you grasp that all sound is just a large addition problem of many, many sine waves, the ability to distinguish between them to a fairly high degree of fidelity feels almost like magic.