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What Is the Fourier Transform?

quantamagazine.org

201–210 of 214 posts

Re: What Is the Fourier Transform?

#201

Earlier quoted context omitted.

When I think of Laplace Transforms I always think of control theory - poles, zeros etc.

My control theory professor (who was also my physics advisor -- it was a small college) explained it like this: Physicists like Fourier transforms because they go from minus to plus infinity, like the universe. Control engineers like Laplace transforms because they start at zero, and a control system also has a starting point.

The two-sided Laplace transform would probably have made his head explode.

Re: What Is the Fourier Transform?

#202
post #170

Can somebody eli5, im an amateur. How does the transform know the frequencies of the output. Do you have to specify a number n, and then it decomposes it into n frequencies. Or do you give it a list of frequencies, and then it decomposes the coefficient or amplitude or something for each? I guess what i want to know, in the examples it always shows like 3 or 4 constituents frequencies as output, but why not hundreds…

Maybe this will help https://dsego.github.io/demystifying-fourier/

Re: What Is the Fourier Transform?

#203
post #75

Earlier quoted context omitted.

Years ago, I often struggled to choose between Amazon products with high ratings from a few reviews and those with slightly lower ratings but a large volume of reviews. I used the Laplace Rule of Succession to code a browser extension to calculate Laplacian scores for products, helping to make better decisions by balancing high ratings with low review counts. https://greasyfork.org/en/scripts/443773-amazon-ranking-la…

Just for reference, in case you find yourself in an optimization under uncertainty situation again: The decision-theoretic right way to do this is generate a bayesian posterior over true ranking given ranking count and a prior on true rankings, add a loss function (it can just be the difference between the true rating of the selected item and the true rating of the non-selected item for simplicity) then choose your o…

Can you please provide an example or link to read more? Seems very interesting.

Re: What Is the Fourier Transform?

#204
post #125

Earlier quoted context omitted.

Did you make sproingies from the tear-off side strips of the printer paper, though? That was the best bit. :P

Of course!

This continued with kids into the 90's. I miss that bit.

https://www.reddit.com/r/nostalgia/comments/b6dptv/folding_t...

Re: What Is the Fourier Transform?

#205

Earlier quoted context omitted.

Well, there are use cases for lossy compression as well as non-lossy, and nobody is saying they are the same. If you really need to heavily compress to reduce file size or transmission bandwidth then you'll likely need to use a lossy CODEC, so the question then becomes how can you minimize the reduction in perceived quality of whatever you are compressing (photos, video, audio), which comes down to how these various…

> large scale detail (corresponding to low frequency FFT components) This isn't true in practice - images are not bandlimited like audio so there aren't really visual elements of images corresponding to low frequency cosine waves. That's why the lowest frequency DCT coefficient in a JPEG image is 16x16 pixels, which is hardly large scale. But you do quantize all components of the DCT transform, not just the highest o…

Sure, but quantization is just another level of lossiness once you've already decided what information to throw away.

In terms of understanding how JPEG compression works, and how it relates to human perception, I'd say that in order of importance it's:

1) Throw away fine detail by discarding high frequency components

2) More heavily compress/discard color than brightness detail (using YUV)

3) Quantize the frequency components you are retaining

Re: What Is the Fourier Transform?

#206
post #107

This is maybe a good first thing to read if you've never heard of the Fourier Transform before, but it makes it sound a great deal more arbitrary and random than it actually is. It might set your understanding back by giving you the illusion that you understand things you don't actually understand, and that would be a shame, because some of those things are more beautiful than a sunrise or a hummingbird. It would be…

As usual, 3 Blue 1 Brown delivers: https://youtu.be/spUNpyF58BY?si=nSqHf_3zbhyu9YGd

3b1b is the xkcd of maths

Re: What Is the Fourier Transform?

#207

Everyone loves the fourier transform because it's easy to understand but everyone ignores the laplace transform, which is much more beautiful, imo, and quite related.

They are quite related, but the Fourier transform seems far more beautiful and generalizable: you can do 2-d, 3-d, etc transforms, and they automatically respect the symmetries of the problems (e.g. rotating the coordinate system rotates the Fourier transform in a corresponding way; frequencies and wave-vectors have meanings). This fully extends to any "nice" abelian group satisfying minor technical conditions, where the mapping is to it's dual group. It even mostly extends to non-abelian groups (representation theory), though some nice properties are lost.

The Laplace transform shines in having nicer convergence properties in some specific cases. While those are extremely valuable for control problems, it really is a much more specialized theory, not nearly as widely applicable. (You can come up with n-d versions. The obvious thing to do is copy the Fourier case and iteratively Laplace transform on each coordinate; the special role of one direction either directly in the unilateral case, or indirectly via growth properties in the bilateral case make it hard to argue that this can develop to something more unifying; the domain isn't preserved under rotation.)

Re: What Is the Fourier Transform?

#208
Before computer was ever invented we learned to make Fourier analysis of complex circuitry by hand. Huge matrixes and sliderules. It was most horrible torture, but bloody nazies of Helsinki Polytechnic insisted we must learn to do this without errors and also fast.

When I first time used computer for this task around 1974 on clanky ASR-33, I felt totally abused and brain-raped.

Re: What Is the Fourier Transform?

#209

Earlier quoted context omitted.

True dat. But you see there's this thing called 'Engineering Maths'. Apparently it's really bad for real mathematicians' blood pressure.

Analytic combinatorics (the rubric where mathematicians would want to place all the region-of-convergence, zeros-poles, etc. analysis of generating functions–formal power/Laurent series–Z transforms that engineering often focuses on) is not exactly easy-going either. Other common methods (relating convolution to multiplication, inverting transforms etc.) would traditionally be comprised under the Operational Calculus…

I forgot to mention the converse also applies. Mathematicians talking about stuff we engineers learned the paint by numbers way makes our heads hurt!

Re: What Is the Fourier Transform?

#210

Earlier quoted context omitted.

Just for reference, in case you find yourself in an optimization under uncertainty situation again: The decision-theoretic right way to do this is generate a bayesian posterior over true ranking given ranking count and a prior on true rankings, add a loss function (it can just be the difference between the true rating of the selected item and the true rating of the non-selected item for simplicity) then choose your o…

Can you please provide an example or link to read more? Seems very interesting.

https://en.m.wikipedia.org/wiki/Decision_theory
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