Continuous-Time Fourier Transform (CTFT)
This is getting into the weeds of signal processing.
Convolution is very expensive. This is convolution
(f∗g)(t)≜∫−∞∞f(τ)g(t−τ)dτ
Let g(t)=eiωt
(f∗g)(t)=∫f(τ)eiω(t−τ)dτ=eiωt∫f(τ)e−iωτdτ
We now call
f~(ω)≜∫−∞∞f(τ)e−iωτdτ
So
(f∗eiωt)(t)=eiωtf~(ω)
The inverse of f~ is
f(t)≜2π1∫−∞∞f^(ω)eiωtdω
We can write
f(t)↔f^(ω)
Cheat sheet
δ(x)↔1
1↔2πδ(k)
eik0x↔2πδ(k−k0)
cos(k0x)↔π[δ(k−k0)+δ(k+k0)]
sin(k0x)↔−iπ[δ(k−k0)−δ(k+k0)]
e−ax2↔aπe−k2/(4a)(Gaussian↔Gaussian)
e−a∣x∣↔a2+k22a(Lorentzian)
f(x−a)↔e−ikaf~(k)(shift↔phase)
eik0xf(x)↔f~(k−k0)(phase↔shift)
f(ax)↔∣a∣1f~(k/a)(narrow↔wide)
f′(x)↔ikf~(k)xf(x)↔if~′(k)
Convolution
(f∗g)(x)↔f~(k)g~(k)f(x)g(x)↔2π1(f~∗g~)(k)