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.
What Is the Fourier Transform?
201–210 of 214 posts
Re: What Is the Fourier Transform?
#202Can 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…
Re: What Is the Fourier Transform?
#203Earlier 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…
Re: What Is the Fourier Transform?
#204Earlier 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!
https://www.reddit.com/r/nostalgia/comments/b6dptv/folding_t...
Re: What Is the Fourier Transform?
#205Earlier 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…
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?
#206This 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
Re: What Is the Fourier Transform?
#207Everyone 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.
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?
#208When 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?
#209Earlier 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…
Re: What Is the Fourier Transform?
#210Earlier 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.