blog:2019:0225_fft_scaling_factor
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blog:2019:0225_fft_scaling_factor [2019/02/26 02:14] – davek | blog:2019:0225_fft_scaling_factor [2022/10/20 16:17] (current) – davek | ||
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====== FFT scaling factor ====== | ====== FFT scaling factor ====== | ||
- | What's often confusing about the FFT is that the transform seems to have numbers that are too big. Let's call this the "FFT scale factor" | + | What's often confusing about the [[https:// |
- | When trying to understand this, the uninitiated user will google something like "FFT scale factor" | + | ====== ====== |
- | But really, these users are trying to figure out *why*, not how. I'm mean, isn' | + | When trying to understand this, the uninitiated user will google something like "FFT scale factor" |
- | The answer is yes, sort of. First off, remember what the first F in FFT standards for: Fast. Maybe users of standard FFT libraries don' | + | But really, these users are trying to figure out **why**, not how. I'm mean, isn' |
- | If you really do care about the absolute power in the frequency-domain bins, you might want to divide by N. Maybe you care about the total energy. Oh wait, you should sum the bins, then divide one time by N! Maybe you only care about the energy of the strongest bin. Just divide that one and ignore the others! | ||
- | As you may realize, even people who do care about the absolute power, don't care about it to the degrees | + | The answer is yes, sort of. First off, remember what the first " |
+ | |||
+ | If you really do care about the absolute power in the frequency-domain bins, you might want to divide by N. Maybe you care about the total energy. Oh wait, you should sum the bins, then divide by N one time! Now it's faster for you, too. Maybe you only care about the energy of the strongest bin. Just divide that one bin by N and ignore the others! | ||
+ | |||
+ | As you may realize, even many people who do care about the absolute power, don't care about it to the degree | ||
So *why* do FFT implementations seem to be off by a factor of N? It's for performance - the FFT is an intermediate result and you should divide by N if and when you need it. | So *why* do FFT implementations seem to be off by a factor of N? It's for performance - the FFT is an intermediate result and you should divide by N if and when you need it. | ||
- | How is an FFT implementation off by N? Google "FFT scale factor" | + | How is an FFT implementation off by N? Google "FFT scale factor" |
{{tag>}} | {{tag>}} | ||
~~LINKBACK~~ | ~~LINKBACK~~ | ||
- | ~~DISCUSSION~~ | + | //~~DISCUSSION~~ |
- | ~~DRAFT~~ | + | |
blog/2019/0225_fft_scaling_factor.1551147258.txt.gz · Last modified: 2021/09/08 17:02 (external edit)