Thursday, 8 December 2016

Discrete-time Fourier Transform of the unit step sequence $u[n]$


From text books we know that the DTFT of $u[n]$ is given by


$$U(\omega)=\pi\delta(\omega)+\frac{1}{1-e^{-j\omega}},\qquad -\pi\le\omega <\pi\tag{1}$$


However, I haven't seen a DSP textbook that at least pretends to give a more or less sound derivation of $(1)$.


Proakis [1] derives the right half of the right-hand side of $(1)$ by setting $z=e^{j\omega}$ in the $\mathcal{Z}$-transform of $u[n]$, and says that it is valid except for $\omega=2\pi k$ (which is of course correct). He then states that at the pole of the $\mathcal{Z}$-transform we have to add a delta impulse with an area of $\pi$, but that appears more like a recipe to me than anything else.


Oppenheim and Schafer [2] mention in this context




Although it is not completely straightforward to show, this sequence can be represented by the following Fourier transform:



which is followed by a formula equivalent to $(1)$. Unfortunately, they didn't take the trouble to show us that "not completely straightforward" proof.


A book that I actually didn't know, but which I found when looking for a proof of $(1)$ is Introduction to Digital Signal Processing and Filter Design by B.A. Shenoi. On page 138 there's a "derivation" of $(1)$, but unfortunately it is wrong. I asked a "DSP-puzzle" question to have people show what is wrong with that proof.]


So my question is:


Can anybody provide a proof/derivation of $(1)$ that is sound or even rigorous while being accessible for mathematically inclined engineers? It doesn't matter if it's just copied from a book. I think it would be good to have it on this site anyway.


Note that even on math.SE almost nothing relevant is to be found: this question has no answers, and that one has two answers, one of which is wrong (identical to Shenoi's argument), and the other one uses the "accumulation property", which I would be happy with, but then one needs to proof that property, which puts you back to the start (because both proofs basically prove the same thing).


As a final note, I did come up with something like a proof (well, I'm an engineer), and I will also post it as an answer some days from now, but I would be happy to collect other published or unpublished proofs that are simple and elegant, and, most importantly, that are accessible for DSP engineers.


PS: I do not doubt the validity of $(1)$, I would just like to see one or several relatively straightforward proofs.





[1] Proakis, J.G. and D.G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 3rd edition, Section 4.2.8

[2] Oppenheim, A.V. and R.W. Schafer, Discrete-Time Signal Processing, 2nd edition, p. 54.






Inspired by a comment by Marcus Müller, I'd like to show that $U(\omega)$ as given by Eq. $(1)$ satisfies the requirement

$$u[n]=u^2[n]\rightarrow U(\omega)=\frac{1}{2\pi}(U\star U)(\omega)$$


If $U(\omega)$ is the DTFT of $u[n]$, then


$$V(\omega)=\frac{1}{1-e^{-j\omega}}$$


must be the DTFT of



$$v[n]=\frac12\text{sign}[n]$$


(where we define $\text{sign}[0]=1$), because


$$V(\omega)=U(\omega)-\pi\delta(\omega)\Longleftrightarrow u[n]-\frac12=\frac12\text{sign}[n]$$


So we have


$$\frac{1}{2\pi}(V\star V)(\omega)\Longleftrightarrow \left(\frac12\text{sign}[n]\right)^2=\frac14$$


from which it follows that


$$\frac{1}{2\pi}(V\star V)(\omega)=\text{DTFT}\left\{\frac14\right\}=\frac{\pi}{2}\delta(\omega)$$


With this we get


$$\begin{align}\frac{1}{2\pi}(U\star U)(\omega)&=\frac{1}{2\pi}\left[(\pi\delta(\omega)+V(\omega))\star (\pi\delta(\omega)+V(\omega))\right]\\&=\frac{1}{2\pi}\left[\pi^2\delta(\omega)+2\pi V(\omega)+(V\star V)(\omega)\right]\\&=\frac{\pi}{2}\delta(\omega)+V(\omega)+\frac{\pi}{2}\delta(\omega)\\&=U(\omega)\qquad\text{q.e.d.}\end{align}$$



Answer




Cedron Dawg posted an interesting initial point in this answer. It begins with these steps:


$$ \begin{align} U(\omega) &= \sum\limits_{n=0}^{+\infty} e^{-j \omega n} \\ &= \lim_{ N \to \infty } \sum\limits_{n=0}^{N-1} e^{-j \omega n}\\ &= \lim_{ N \to \infty } \left[ \frac{ 1 - e^{-j \omega N} }{ 1 - e^{-j \omega } } \right] \\ &= \frac{ 1 }{ 1 - e^{-j \omega } } - \lim_{ N \to \infty } \left[ \frac{ e^{-j \omega N} }{ 1 - e^{-j \omega } } \right] \end{align} $$


It turns out the term inside the limit can be expanded as follows:


$$\begin{aligned} \frac{ e^{-j \omega N} }{ 1 - e^{-j \omega } } ={} &\frac{1}{\sin^2(\omega)+(1-\cos(\omega))^2} \cdot \\ &\left[-\cos(\omega)\cos(N\omega)+\cos(N\omega)-\sin(\omega)\sin(N\omega)+ \\ j(-\sin(\omega)\cos(N\omega)+\cos(\omega)\sin(\omega)-\sin(N\omega))\right] \end{aligned} $$


The common factor outside the brackets can be expressed as:


$$\frac{1}{\sin^2(\omega)+(1-\cos(\omega))^2} = \frac{1}{4\sin^2(\omega/2)}$$


The real part inside the brackets also equals:


$$-\cos(\omega)\cos(N\omega)+\cos(N\omega)-\sin(\omega)\sin(N\omega)= 2\sin(\omega/2)\sin[\omega(-N+1/2)]$$


On the other hand, the imaginary part can be rewritten as:


$$-\sin(\omega)\cos(N\omega)+\cos(\omega)\sin(\omega)-\sin(N\omega)=-2\sin(\omega/2)\cos[\omega(-N+1/2)]$$



Rewritting the original term we get that:


$$\begin{align} \frac{ e^{-j \omega N} }{ 1 - e^{-j \omega } } &=\frac{2\sin\left(\frac \omega 2\right)}{4\sin^2\left(\frac \omega 2\right) } \left( \sin[\omega(-N+1/2)] - j\cos[\omega(-N+1/2)]\right) \\ &=-\frac{\sin[\omega(M+1/2)]}{2\sin\left(\frac \omega 2\right)} - j\frac{\cos[\omega(M+1/2)]}{2\sin\left(\frac \omega 2\right)} \end{align} $$


where I used $M=N-1$ and the limit stays unaffected as $M\to \infty$ as well.


According to the 7th definition in this site:


$$\lim_{M\to \infty} -\frac{1}{2\sin(\omega/2)}\sin[\omega(M+1/2)] = -\pi \delta(\omega)$$


So far we have that:


$$\lim_{ M \to \infty } \frac{ e^{-j \omega (M+1)} }{ 1 - e^{-j \omega } } =-\pi\delta(\omega) -j\lim_{M\to \infty} \frac{\cos[\omega(M+1/2)]}{2\sin(\omega/2)} $$


If we could prove that the second term on the right of the equality is $0$ in some sense, then we are done. I asked it at math.SE and, indeed, that sequence of functions tends to the zero distribution. So, we have that:


$$ \begin{align} U(\omega) &= \frac{ 1 }{ 1 - e^{-j \omega } } - \lim_{ N \to \infty } \left[ \frac{ e^{-j \omega N} }{ 1 - e^{-j \omega } } \right] \\ &=\frac{ 1 }{ 1 - e^{-j \omega } }+\pi\delta(\omega) +j\lim_{M\to \infty} \frac{\cos[\omega(M+1/2)]}{2\sin(\omega/2)} \\ & =\frac{ 1 }{ 1 - e^{-j \omega } }+\pi\delta(\omega) \end{align} $$


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