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Fourier transforms express a function in terms of continuous frequencies, making them essential in calculus, differential equations, signal processing, and physics. This cheat sheet summarizes the angular frequency convention, where frequency is measured by ω\omega in radians per unit. It helps students quickly compare definitions, properties, and common transform pairs without searching through a textbook. The reference is especially useful when solving integrals, analyzing linear systems, or converting differential equations into algebraic equations. The main formulas are the forward transform F(ω)=f(t)eiωtdtF(\omega)=\int_{-\infty}^{\infty} f(t)e^{-i\omega t}\,dt and the inverse transform f(t)=12πF(ω)eiωtdωf(t)=\frac{1}{2\pi}\int_{-\infty}^{\infty} F(\omega)e^{i\omega t}\,d\omega. Core ideas include linearity, scaling, shifting, differentiation, convolution, and energy preservation through Parseval's theorem. Common pairs such as Gaussians, exponentials, rectangular pulses, sines, cosines, and delta functions provide fast shortcuts for computation. The most important skill is matching the convention and applying each property with the correct constants.

Key Facts

  • Using the angular frequency convention, the Fourier transform is F(ω)=F{f(t)}=f(t)eiωtdtF(\omega)=\mathcal{F}\{f(t)\}=\int_{-\infty}^{\infty} f(t)e^{-i\omega t}\,dt.
  • The inverse Fourier transform is f(t)=F1{F(ω)}=12πF(ω)eiωtdωf(t)=\mathcal{F}^{-1}\{F(\omega)\}=\frac{1}{2\pi}\int_{-\infty}^{\infty} F(\omega)e^{i\omega t}\,d\omega.
  • Linearity means F{af(t)+bg(t)}=aF(ω)+bG(ω)\mathcal{F}\{af(t)+bg(t)\}=aF(\omega)+bG(\omega) for constants aa and bb.
  • Time shifting gives F{f(tt0)}=eiωt0F(ω)\mathcal{F}\{f(t-t_0)\}=e^{-i\omega t_0}F(\omega), while frequency shifting gives F{eiω0tf(t)}=F(ωω0)\mathcal{F}\{e^{i\omega_0 t}f(t)\}=F(\omega-\omega_0).
  • Scaling gives F{f(at)}=1aF(ωa)\mathcal{F}\{f(at)\}=\frac{1}{|a|}F\left(\frac{\omega}{a}\right) for a0a\ne 0.
  • Differentiation in time becomes multiplication in frequency: F{f(t)}=iωF(ω)\mathcal{F}\{f'(t)\}=i\omega F(\omega) when boundary terms vanish.
  • Convolution in time becomes multiplication in frequency: F{(fg)(t)}=F(ω)G(ω)\mathcal{F}\{(f*g)(t)\}=F(\omega)G(\omega), where (fg)(t)=f(τ)g(tτ)dτ(f*g)(t)=\int_{-\infty}^{\infty} f(\tau)g(t-\tau)\,d\tau.
  • Parseval's theorem states f(t)2dt=12πF(ω)2dω\int_{-\infty}^{\infty}|f(t)|^2\,dt=\frac{1}{2\pi}\int_{-\infty}^{\infty}|F(\omega)|^2\,d\omega.

Vocabulary

Fourier transform
A transform that rewrites a function f(t)f(t) as a frequency-domain function F(ω)F(\omega) using complex exponentials.
Inverse Fourier transform
The operation that reconstructs f(t)f(t) from F(ω)F(\omega) using f(t)=12πF(ω)eiωtdωf(t)=\frac{1}{2\pi}\int_{-\infty}^{\infty}F(\omega)e^{i\omega t}\,d\omega.
Angular frequency
The frequency variable ω\omega measured in radians per unit, related to ordinary frequency by ω=2πf\omega=2\pi f.
Convolution
An integral combination of two functions defined by (fg)(t)=f(τ)g(tτ)dτ(f*g)(t)=\int_{-\infty}^{\infty}f(\tau)g(t-\tau)\,d\tau.
Dirac delta function
A generalized function δ(t)\delta(t) with the sifting property f(t)δ(ta)dt=f(a)\int_{-\infty}^{\infty}f(t)\delta(t-a)\,dt=f(a).
Transform pair
A matched pair f(t)F(ω)f(t)\leftrightarrow F(\omega) showing a function and its Fourier transform under a chosen convention.

Common Mistakes to Avoid

  • Mixing Fourier transform conventions is wrong because the factors of 2π2\pi change between definitions. If F(ω)=f(t)eiωtdtF(\omega)=\int f(t)e^{-i\omega t}\,dt, then the inverse must include 12π\frac{1}{2\pi}.
  • Forgetting the absolute value in scaling gives the wrong amplitude. The correct rule is F{f(at)}=1aF(ωa)\mathcal{F}\{f(at)\}=\frac{1}{|a|}F\left(\frac{\omega}{a}\right), not 1aF(ωa)\frac{1}{a}F\left(\frac{\omega}{a}\right) in all cases.
  • Reversing the sign in the time-shift factor changes the phase in the wrong direction. The correct formula is F{f(tt0)}=eiωt0F(ω)\mathcal{F}\{f(t-t_0)\}=e^{-i\omega t_0}F(\omega).
  • Treating convolution as ordinary multiplication in the time domain loses the integral structure. The convolution (fg)(t)(f*g)(t) transforms to F(ω)G(ω)F(\omega)G(\omega), but f(t)g(t)f(t)g(t) does not transform to F(ω)G(ω)F(\omega)G(\omega).
  • Ignoring distribution terms for constants and sinusoids leads to incomplete answers. For example, F{1}=2πδ(ω)\mathcal{F}\{1\}=2\pi\delta(\omega) and F{eiω0t}=2πδ(ωω0)\mathcal{F}\{e^{i\omega_0 t}\}=2\pi\delta(\omega-\omega_0).

Practice Questions

  1. 1 Find F{eat}\mathcal{F}\{e^{-a|t|}\} for a>0a>0 using F(ω)=f(t)eiωtdtF(\omega)=\int_{-\infty}^{\infty}f(t)e^{-i\omega t}\,dt.
  2. 2 If F{f(t)}=F(ω)\mathcal{F}\{f(t)\}=F(\omega), find the Fourier transform of 3f(2t4)3f(2t-4) in terms of F(ω)F(\omega).
  3. 3 Use the differentiation property to transform the differential equation y(t)4y(t)=g(t)y''(t)-4y(t)=g(t) into an algebraic equation involving Y(ω)Y(\omega) and G(ω)G(\omega), assuming boundary terms vanish.
  4. 4 Explain why a narrow pulse in the time domain tends to have a broad Fourier transform in the frequency domain.