The definitions of the Fourier transform and inverse Fourier transform I learned in college were
$$ F(j\omega) = \int_{-\infty}^{\infty} f(t) e^{-j\omega t}\ dt $$ $$ f(t)=\frac{1}{2\pi}\int_{-\infty}^{\infty}F(j\omega)e^{j\omega t} d\omega $$
The salient characteristics of this convention are
- Non-unitary transform; frequency-domain units are radians (variable is $\omega$)
- "Time-domain" units are in time (variable is $t$)
- Function transforms are denoted by capital letters ($F$ vs. $f$)
- The $j$ in $F(j\omega)$ strictly denotes that the function is a Fourier transform
- And of course, the usual EE convention that $j=\sqrt{-1}$.
Nowadays I use a much different convention, essentially that used on the wikipedias:
$$ \hat{f}(\xi) = \int_{-\infty}^{\infty} f(x) e^{-j2\pi\xi x}dx $$ $$ f(x) = \int_{-\infty}^{\infty} \hat{f}(\xi) e^{j2\pi\xi x} d\xi $$ The characteristics of this convention are
- Unitary transform; frequency-domain units are normalized frequency (variable is $\xi$)
- "Time-domain" units are unitless (variable is $x$)
- Function transforms wear hats ($\hat{f}$ vs. $f$)
- Variables in the Greek alphabet denote transformed variables in the Latin alphabet ($\xi$ vs. $x$)
I greatly prefer this convention for several reasons.
- Using a unitary convention greatly increases the symmetry and clarity of Fourier duals:
compare
- $\mathrm{rect}(x)\leftrightarrow\mathrm{sinc}(\xi)$,
- $\mathrm{sinc}(x)\leftrightarrow\mathrm{rect}(\xi)$ to
- $\mathrm{rect}(t)\leftrightarrow\mathrm{sinc}(\frac{\omega}{2\pi})$,
- $\mathrm{sinc}(t)\leftrightarrow\mathrm{rect}(\frac{\omega}{2\pi})$.
- Using $x$ instead of $t$ for the "time-domain" variable makes the equations more agnostic of one's problem domain. This makes it much easier to analogize about 2D image processing concepts in terms of 1D signal processing concepts, without the cognitive dissonance of using $t$ as a variable representing distance, or having to change variables around when going from one domain to the other.
- I find capital letters to be more useful for denoting discrete-valued variables/functions than for representing transformed functions.
- Using the hat more clearly denotes the Fourier transform as an operator that is applied to $f$, where the resulting function accepts a frequency-domain parameter $\xi$. Compare this to the far more ungainly $\mathcal{F}\{f\}$, the "traditional" way I learned in college to denote the Fourier transform as an operator, which just seemed way too confusing to me at the time ($\mathcal{F}{f(t)}$ vs $\mathcal{F}\{f\}(t)$ vs $\mathcal{F}\{f\}(\omega)$ etc.)
- I generally found that doing signal processing analysis with radians just sprinkled a lot more $\pi$s around than I felt necessary. Using units of normalized frequency makes a lot more sense to me, particularly when working through problems involving sampling theory.
Of course, it would be quite vain of me to consider my choice of convention to be superior to that used by others. But I'm having a hard time coming up with good reasons to prefer the convention I originally learned in college (ie, reasons that don't involve tradition).
Presently, I can think of one decent reasons for preferring the "traditional" convention: Using the non-unitary transform, and the $F(j\omega)$ parameter notation, greatly improves notaional consistency with the Laplace transform. Also, hats might be easier to lose/confuse than capital letters.
Can anybody think of other reasons to prefer the "traditional" (non-unitary) convention? Is this "traditional" convention the same as what you learned a signal processing course (if you took one)? Which convention do you prefer?