Is there a reason why most people use the normalization $$ \hat{f}(x) = \int_{\infty}^{\infty} e^{ 2 \pi i t x} \cdot f(t) d t $$ instead of $$ \hat{f}(x) = \int_{\infty}^{\infty} e^{2 \pi i t x} \cdot f(t) d t \text{ } ? $$ I've just finished writing a paper where I've used the second definition, and I'm wondering now, if I should rewrite it. The paper is in analytic number theory.
There are many variations of the definition of the Fourier transform and its inverse that are all essentially equivalent. For example, the factor of $2\pi$ often appears as $1/(2\pi)$ in front of the integral in one of the transform pair, or as $1/\sqrt{2\pi}$ in front of both integrals in the transform pair. Researchers in different fields have often adopted a particular convention. If you want to publish in a journal where such a convention is well established, then you will probably find that it is easier to get your paper accepted for publication if you follow the convention used by people working in that field. 


I think I've come to the personal concensus, that with the choice of notation $$ \hat{f}(x) = \int_{\infty}^{\infty} e^{ 2 \pi i t x} f(t) d t $$ we are extracting information from $f$, while with the notation $$ \hat{f}(x) = \int_{\infty}^{\infty} e^{2 \pi i t x} f(t) d t $$ we are generating information from the function $f$. For example, if $f$ were the probability density of a distribution I would go with the second notation to denote the characteristic function of the distribution. This aligns with the standard notation for the fourier transform of a probability distribution (check "characteristic function" on wiki). Anybody with me on this? P.S: I've seen both conventions used in my field. I believe the choice has to do with the perspective you take on the role of $f$. Do you want to understand $f$ better or do you want to generate things from $f$ and are actually interested in $\hat{f}$ rather than $f$? 


$c_n = \int_0^1 f(x)e^{2\pi i{n}x}\,dx$
. Notice the appearance of the sign in this coefficient formula, which is the Fourier transform $\widehat{f} \colon {\mathbf Z} \rightarrow {\mathbf C}$: $\widehat{f}(n) = c_n$. – KConrad May 28 '12 at 4:05