Someone redpill me on the fourier transform please.
Someone redpill me on the fourier transform please
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additive synthesis
On compact topological groups it's a corollary of Peter-Weyl theorem. On locally compact abelian groups it's a corollary of the definition of the Pontryagin dual.
wtf! i'm a #wildbergermissile now
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>Someone redpill me on the fourier transform please.
>Someone teach me the real truth, hidden by blue-pilled PC culture, on fourier transform please
No. Learn the blue-pill version.
lol i was thinking the same thing, user
It's like doing Fourier series but the period is over the entire number line.
>red pill
Fuck off back to /pol/
OP was asking about the anabelian case though
ah godammit
Ignoring the SJWtard Bern victim shitposters.
this is a good one :
youtube.com
Also Khanacademy is your friend.
The Fourier transform describes a way of decomposing a function into a sum of orthogonal basis functions in just the same way as we decompose a point in Euclidean space into the sum of its basis vector components.
some operations are just easier in the frequency domain. OTOH why is it so hard to read wikipedia?
acko.net
That's not red-pill Fourier Transform, that's blue-pill standard even-the-worst-SJWs-believe-it Fourier Transform.
Khanacademy have better examples. That should be OPs primary source.
>redpill me
get out, /pol/esmoker
>He thinks pajeet academy can teach him anything
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>Pajeet is beginning to spill out of /g/
Mathematically, it's really confusing
practically, it's really simple. Basically, all signals are made of other baby signals. A fourier transform gets the baby signals out of the big daddy signal.
It really isn't. If you don't mind the engineering angle, it's like synchronous radio receiver, tuning to a desired frequency by multiplying the input by a sinusoid. It's just that you're trying infinite number of frequencies at once, and using complex corkscrew functions instead of sinusoids.
I also like the duality angle, e.g. wide signals in the time domain have narrow frequency domain representation and vice versa. E.g a sine transformed is a single value.
It works especially well on the Gaussian function.
A rainbow is the Fourier transform of sunlight.