Timeline for Radix2 Fast Fourier Transform implemented in C++
Current License: CC BY-SA 4.0
9 events
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Aug 27, 2019 at 4:31 | comment | added | Nayuki | @tjwrona1992 Regarding Bluestein, the modulo is useful because it makes floating-point trigonometry more accurate. Basically if you look at sin(0.1) versus sin(0.1 + 2*PI) when calculated on a computer, the former is more accurate due to finite floating-point precision. So I chose to do a reduction over integers (which is exact) before calling the trigonometric function. | |
Aug 26, 2019 at 20:20 | comment | added | tjwrona |
If you don't mind me asking, what is the reason for the temp %= static_cast<unsigned long long>(n) * 2; line in your Bluestein FFT implementation? I've been working on a Bluestein implementation of my own and I can't quite figure out why that line is necessary.
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Aug 19, 2019 at 0:59 | history | edited | Nayuki | CC BY-SA 4.0 |
added 862 characters in body
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Aug 18, 2019 at 21:33 | comment | added | tjwrona | bullet 5, I actually stumbled across that library when I was part-way through writing mine and used it as a reference. It was VERY helpful! Thank you! :) | |
Aug 18, 2019 at 21:32 | comment | added | tjwrona | bullet 4, could you possibly elaborate on this? I'm not sure I fully understand what you mean by this but it sounds interesting | |
Aug 18, 2019 at 21:32 | comment | added | tjwrona | bullet 3 I agree, I will likely add using statements because it is a bit cumbersome haha | |
Aug 18, 2019 at 21:32 | comment | added | tjwrona | bullet 2 is interesting and I'll have to do more research on that. I'm still fairly inexperienced when it comes to DSP algorithms, but I'm working my way through a book and learning a lot. | |
Aug 18, 2019 at 21:31 | comment | added | tjwrona | Thanks @Nayuki! There is a lot here so I will reply with a comment per bullet. I have done some refactoring already which took care of bullet 1. | |
Aug 18, 2019 at 17:28 | history | answered | Nayuki | CC BY-SA 4.0 |