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Homework 3 Solution, ECE438, Fall 2014
Question 1
Let x(t) be a continuous-time signal and let y[n]=x(nT) be a sampling of that signal with period T>0. We would like to interpolate the samples (i.e., "connect the dots") in order to try to recover x(t).
a) Derive a formula for a band-limited interpolation of the samples (i.e., an expression for a continuous signal z(t) in terms of the samples y[n]). (Do not simply write down the formula; show how to derive it.)
Solution
To begin, we can write express the ideally sampled signal, x_s(t), as
$ \begin{align} x_s(t)&=comb_T \left \{ x(t) \right \}\\ &= x(t)\sum_{n=-\infty}^{\infty} \delta(t-kT) \end{align} $
We can then get the spectrum as
$ \begin{align} X_s(f) &= CTFT \left \{ comb_T \left \{ x(t) \right \} \right \} \\ &= \frac{1}{T} rep_{\frac{1}{T}} \left \{ X(f) \right \}\\ &=\frac{1}{T} \sum_{k=-\infty}^{\infty}X(f-k\frac{1}{T}) \end{align} $
The interpolation filter should filter out the copies of the original spectrum while preserving the one at baseband. Conceptually, the simplest filter is
$ H_r(f)=\begin{cases} T \mbox{, where } |f| \leq \frac{1}{2T} \\ 0 \mbox{, else}\end{cases} $
$ h_r(t) = sinc\left ( \frac{t}{T} \right ) $
Performing the convolution in the time domain
$ \begin{align} z(t) &= comb_{T_s} \{ x(t) \} \ast sinc \left ( \frac{t}{T} \right ) \\ &=\left ( \sum_{n=-\infty}^{\infty} x(nT) \delta (t-nT) \right )\ast sinc \left ( \frac{t}{T} \right ) \\ &=\sum_{n=-\infty}^{\infty} x(nT) sinc \left (\frac{t-nT }{T}\right) \\ \end{align} $
b) Show that your interpolation is equal to the original signal at all sample points.
Solution
Looking at the mth sample point
$ \begin{align} z(mT) &=\sum_{n=-\infty}^{\infty} x(nT) sinc \left (\frac{mT-nT }{T}\right) \\ &=\sum_{n=-\infty}^{\infty} x(nT) sinc \left (m-n \right) \mbox{, where } sinc(m-n) = \begin{cases} 1 \mbox{, where } m=n \\ 0 \mbox{, else}\end{cases} \\ &= x(mT) \end{align} $
c) Under what circumstances is your interpolation equal to the original signal x(t)? Explain.
Solution
The original signal, x(t), must be bandlimited, so that X(f) = 0 for all f>1/2T. Otherwise, there might be aliasing.
Question 2
Again, we consider a continuous-time signal x(t) and a sampling y[n]=x(nT) of that signal.
a) Write a formula for a piece-wise constant interpolation of the samples.
Solution
The basic reconstruction segment we will use for the piece-wise constant interpolation is
$ s_R(t) = rect \left ( \frac{t-\frac{T}{2}}{T} \right ) $
This segment will be weighted and shifted for each sample point. For example, the nth sample point would produce
$ \begin{align} s_{R,n} (t) &= x(nT) rect\left( \frac{t-\frac{T}{2} - nT}{T} \right)\\ &= x(nT) \left ( rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \ast \delta(t-nT) \right ) \\ &= rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \ast \left (x(nT) \delta(t-nT)\right) \end{align} $
Extending this for all n, we get
$ \begin{align} x_R(t) &= \sum_{n=-\infty}^{\infty} rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \ast \left (x(nT) \delta(t-nT)\right) \\ &= rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \ast \sum_{n=-\infty}^{\infty} \left (x(nT) \delta(t-nT)\right) \\ &= rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \ast comb_T \left \{ x(t) \right \} \end{align} $
The last line helps with part b.
b) Derive the relationship between the Fourier transform of the interpolation you wrote in 2a) and the Fourier transform of x(t). (Do not simply write down the formula; show how to derive it.)
Solution
$ \begin{align} X_R(f) &= CTFT \left \{ rect \left ( \frac{t-\frac{T}{2}}{T} \right ) \right \} CTFT \left \{ comb_T \left \{ x(t) \right \} \right \} \\ &= e^{-j2\pi f \frac{T}{2}} T sinc(Tf) \frac{1}{T} rep_{\frac{1}{t}}\left \{ X(f) \right \} \\ & = e^{-j \pi f T} sinc(Tf) rep_{\frac{1}{t}}\left \{ X(f) \right \} \end{align} $
c) Is the interpolation you wrote in 2a) band-limited? Explain.
Solution
No, it is not band-limited. For one, the rep function replicates the spectrum every 1/T, and the sinc is not bandlimited.
Question 3
Let
$ x(t)=7 \text{sinc } ( \frac{t-5}{2} ). $
a) Obtain the Fourier transform X(f) of the signal and sketch the graph of |X(f)|.
Solution
To solve this, we will use the transform of a sinc, as well as the scaling and shifting properties:
$ \begin{align} sinc(t) &\leftrightarrow rect(f) \\ x(at) &\leftrightarrow \frac{1}{|a|} X(af) \\ x(t-t_0) &\leftrightarrow e^{-j2\pi f t_0}X(f) \end{align} $
In our case, t_0=5 and a=2, so
$ \begin{align} X(f) &= CTFT \left \{7sinc\left ( \frac{x-5}{2} \right ) \right \} \\ &= 7\cdot 2 e^{-j2\pi f 5} rect(2f) \\ &= 14 e^{-j10\pi f} rect(2f) \\ \end{align} $
b) What is the Nyquist rate $ f_0 $ for this signal?
Solution
The Nyquist rate is 1/4 Hz (twice the maximum non-zero frequency).
c) Let
$ T = \frac{1}{3 f_0}. $
Write a mathematical expression for the Fourier transform $ X_s(f) $ of
$ x_s(t)= \text{ comb}_T \left( x(t) \right). $
Sketch the graph of $ |X_s(f)| $.
Solution
$ \begin{align} X_s(f) &= \text{CTFT} \left \{ \text{comb}_T \left \{ x(t) \right \} \right \} \\ &= \frac{1}{T} \text{rep}_{\frac{1}{T}} \left \{ X(f) \right \} \\ &= 3f_0 \text{rep}_{3f_0} \left \{ X(f) \right \} \\ &= \frac{3}{4} \text{rep}_{\frac{3}{4}} \left \{ 14 \text{rect}( 2f )\right \} \\ &= \frac{21}{2} \sum_{k=-\infty}^{\infty} \text{rect}\left ( 2f - \frac{3}{4}k\right ) \end{align} $
d) Let
$ T = \frac{1}{5 f_0}. $
Write a mathematical expression for the Fourier transform $ {\mathcal X}_d(\omega) $ of $ x_d[n]= x(nT) $ and sketch the graph of $ |{\mathcal X}_d(\omega)| $.
Solution
The relationship between the DTFT of $ x_d[n] $ and the CTFT of $ x_s(t) $ is
$ X_d(\omega) = X_s\left (\frac{\omega F_s}{2\pi} \right ) $
Therefore
$ \begin{align} X_d(\omega) &= \frac{21}{2} \sum_{k=-\infty}^{\infty} \text{rect}\left ( \frac{5\omega}{4\pi} - \frac{5}{4}k\right ) \\ &= \frac{21}{2} \sum_{k=-\infty}^{\infty} \text{rect}\left ( \frac{5}{4} \frac{1}{2\pi} \left ( 2\omega- 2 \pi k \right )\right ) \end{align} $
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