*Continuous time Fourier transform and Laurent series:*

I recall equations (1) and (2), for convenience set $a=0$, and substitute $z=e^{it/T}$. The function $g(t)=f(e^{it/T})$, with $t\in(-\pi T,\pi T)$, is periodic with period $2\pi T$, given by the Laurent series
$$g(t)=\sum_{n=-\infty}^\infty c_n e^{int/T},$$
with coefficients
$$c_n=\frac{1}{2\pi T}\int_{-\pi T}^{\pi T}g(t)e^{-int/T}\,dt.$$
For $T\gg t$ the sum over $n$ may be approximated by an integral over $\omega=n/T$ with coefficients $C(\omega)=Tc_{n=\omega T}$, giving
$$g(t)=\int_{-\infty}^\infty C(\omega) e^{i\omega t}d\omega,$$
$$C(\omega) =\frac{1}{2\pi}\int_{-\infty}^\infty g(t)e^{-i\omega t}\,dt.$$

In this way the Fourier integral can be obtained as the limit of the Laurent series when the periodicity of the function tends to infinity. Notice that the exponent $nt/T$ cannot be set to zero because, even though $t/T\ll 1$, the product $nt/T=\omega t$ need not be small.

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*Discrete Fourier transform and Laurent series:*

We now start from a discrete time signal $x_n$ and construct the <A HREF="https://en.wikipedia.org/wiki/Z-transform">Z-transform</A>
$$X(z)=\sum_{n=-\infty}^\infty x_{n}z^{-n}=\sum_{n=-\infty}^\infty x_{-n}z^n.$$
This is a Laurent series centered at $a=0$, with inversion formula
$$x_{n}=\frac{1}{2\pi i}\oint X(z)x^{z-1}\,dz.$$
For the discrete Fourier transform one has only $N$ nonzero values of $x_n$, the set $\{x_0,x_1,x_2,\ldots x_{N-1}\}$. The Fourier transform is the set of $N$ variables $X_k=X(z=e^{2\pi ik/N})$ with $k\in\{0,1,2,\ldots N-1\}$. So in this case it's the Z-transform that makes the connection between the Laurent series and the Fourier transform.