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For digital signals, the fourier transform is taken along the unit circle of the Z-transform.
The equivalent to the Z-transform in continuous signals is the Laplace transform, but in that case the fourier transform is taken along the imaginary axis.

Why the difference? Why don't we take the z-transform along the imaginary axis in the DTFT?
An usual intuition to learn is that the real axis in Laplace are exponentials ($e^x$), while the imaginary are sinusoids $e^{iy} = \cos(y) + i\sin(y)$. Wouldnt that relationship hold in Z-transform too?

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One way to see this is to consider the Laplace transform of a sampled signal:

$$x_d(t)=\sum_{n=0}^{\infty}x(nT)\delta(t-nT)\tag{1}$$

where I've assumed that $x(t)$ starts at $t=0$. $T$ is the sampling period, and $\delta(t)$ is the Dirac delta impulse.

Taking the Laplace transform of $(1)$ gives

\begin{align*} X_d(s) &= \int_0^{\infty}\sum_{n=0}^{\infty}x(nT)\delta(t-nT)e^{-st}dt \\ &= \sum_{n=0}^{\infty}x(nT)\int_{0}^{\infty}\delta(t-nT)e^{-st}dt \\ &= \sum_{n=0}^{\infty}x(nT)e^{-snT}\tag{2} \end{align*}

Evaluating $(2)$ on the imaginary axis $s=j\omega$ results in the DTFT of the sampled signal:

$$X_d(j\omega)=\sum_{n=0}^{\infty}x(nT)e^{-j\omega nT}\tag{3}$$

In $(3)$ it is obvious that by varying $\omega$ we move along the unit circle. $X_d(j\omega)$ is periodic with period $2\pi/T$, and for this reason it is frequently written as a function of $e^{j\omega}$.

Setting $e^{sT}=z$ in $(2)$ gives us the $\mathcal{Z}$-transform of the sequence $x(nT)$.

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  • $\begingroup$ Thank you! This is maybe the best explaination for it I have seen. Too shame there's so little focus on this in DSP classes. $\endgroup$ Commented Dec 16, 2024 at 11:03
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    $\begingroup$ Oppenheim & Schafer's Digital Signal Processing used this approach way back in the Beginning Times. If you're burrowing into "why", you can reflect on the fact that the answer is really about aliasing, and how it changes the math. $\endgroup$ Commented Dec 16, 2024 at 16:00

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