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Exercise 5.2Z: DFT of a Triangular Pulse

From LNTwww

Discretisation of a triangular pulse

Consider the sketched triangular pulse

x(t)={A(1|t|/T)0forfor|t|T,|t|>T.

The signal parameters have the following values:

  • amplitude  A=4 V,
  • equivalent pulse duration  Δt=T=1ms.


The spectrum  X(f)  is obtained by applying  the first Fourier Integral:

X(f)=ATsi2(πfT)withsi(x)=sin(x)/x.

The spectral function is now to be approximated by a  Discrete Fourier Transform  (DFT)  with  N=8 , where the   N  coefficients for the time domain   ⇒   d(0), ... , d(7)  can be taken from the graph.

The corresponding spectral coefficients  D(0), ... ,  D(7)  are to be determined.  For the indices  μ=0, ... , N–1  applies:

D(\mu) = \frac{1}{N} \cdot \sum_{\nu = 0 }^{N-1} d(\nu)\cdot {w}^{\hspace{0.05cm}\nu \hspace{0.05cm} \cdot \hspace{0.05cm}\mu} \hspace{0.05cm}.

If we denote the distance between two samples in the time domain by  T_{\rm A}  and the corresponding frequency distance between two lines by f_{\rm A}, following relationship applies:

N \cdot f_{\rm A} \cdot T_{\rm A} = 1 \hspace{0.05cm}.




Hints:




Question

1

Give the time coefficients. What are the values of  d(0)d(3)  and  d(6)?

d(0)\ = \

 \text{V}
d(3)\ = \

 \text{V}
d(6)\ = \

 \text{V}

2

What is the distance  T_{\rm A}  between two time samples?

T_{\rm A}\ = \

 \text{ms}

3

What is the distance  f_{\rm A}  between two DFT frequency samples?

f_{\rm A}\ = \

 \text{kHz}

4

Calculate the coefficient  D(0)  and interpret the result.

D(0)\ = \

 \text{V}

5

Calculate the coefficient  D(2)  and interpret the result, also in terms of the coefficients  D(4)  and  D(6).

D(2)\ = \

 \text{V}

6

Calculate and interpret the DFT coefficient  D(7).

D(7)\ = \

 \text{V}


Solution

(1)  From the graph the following values result with  A = 4 \ {\rm V} :

{d(0) = 4\,{\rm V}, \hspace{0.1cm}d(1) = d(7) = 3\,{\rm V}, \hspace{0.1cm} \hspace{0.1cm}d(2) = d(6) = 2\,{\rm V}, \hspace{0.1cm} \hspace{0.1cm}d(3) = d(5) = 1\,{\rm V}, \hspace{0.1cm} \hspace{0.1cm}d(4) = 0}\hspace{0.05cm}.
\Rightarrow \hspace{0.15 cm}\underline{d(0) = 4\,{\rm V}, \hspace{0.1cm}d(3) = 1\,{\rm V}, \hspace{0.1cm}d(6) = 2\,{\rm V}. \hspace{0.1cm}} \hspace{0.05cm}


(2)  According to the diagram  T_{\rm A} = T/4.

  • With  T = 1 \ \text{ms}  one obtains  \underline{T_{\rm A} = 0.25 \ \text{ms}}.


(3)  For the distances of the samples in the time and frequency domain applies:

N \cdot f_{\rm A} \cdot T_{\rm A} = 1 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}f_{\rm A}= \frac{1}{ 8 \cdot 0.25\, {\rm ms}}\hspace{0.15 cm}\underline{= 0.5\, {\rm kHz}}\hspace{0.05cm}.


(4)  With  N = 8  and  \mu = 0 , it follows from the DFT equation:

D(0) = \frac{1}{8}\cdot \sum_{\nu = 0 }^{7} d(\nu) = \frac{1\,{\rm V}}{8}\cdot (4+3+2+1+0+1+2+3)\hspace{0.15 cm}\underline{= 2 \,{\rm V}}\hspace{0.05cm}.
  • The DFT value D(0) describes the spectral value at  f = 0, where the following relation holds:
X(f=0) = \frac{D(0)}{f_{\rm A}}= \frac{ 2\,{\rm V}}{0.5\,{\rm kHz}}= 4 \cdot 10^{-3}\,{\rm V/Hz}\hspace{0.05cm}.
  • This value agrees with the theoretical value   (A \cdot T) .


(5)  With  N = 8  and  \mu = 2  we obtain:

D(2) = \frac{1}{8}\cdot \sum_{\nu = 0 }^{7} d(\nu)\cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \frac{1}{8}\cdot \sum_{\nu = 0 }^{7} d(\nu)\cdot (-{\rm j})^{\nu} \hspace{0.3cm} \Rightarrow \hspace{0.3cm} = \frac{1\,{\rm V}}{8}\cdot (4-3\cdot{\rm j}-2+{\rm j}-{\rm j}-2+3\cdot{\rm j})\hspace{0.15 cm}\underline{= 0}\hspace{0.05cm}.

This result could have been predicted without calculation:

  • The DFT coefficients  D(\mu)  are at the same time the Fourier coefficients of the function  x_{\rm Per}(t)  periodised at the distance  T_{\rm P} = 2T.
    This is shown as a dashed line in the graph on the information page.
  • Due to symmetry properties, however, all even Fourier coefficients of the function  x_{\rm Per}(t)  are equal to zero   ⇒   D(4)\hspace{0.15cm}\underline{=0},   D(6)\hspace{0.15cm}\underline{=0}.


(6)  The coefficient  D(7)  describes the periodised spectral function at the frequency  f = 7 \cdot f_{\rm A}.  Due to periodicity and symmetry property holds:

D(7) = D(-1) = D^{\star}(1) \hspace{0.05cm}.

Preferably, we calculate this DFT coefficient:

D(1) = \frac{1}{8}\cdot \sum_{\nu = 0 }^{7} d(\nu)\cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \frac{1\,{\rm V}}{8}\cdot \left(4 +3\cdot \frac{1 - {\rm j}}{\sqrt{2}}-2\cdot {\rm j}+ \frac{-1 - {\rm j}}{\sqrt{2}}-{\rm j}+ \frac{-1 + {\rm j}}{\sqrt{2}}-{\rm j}+ 2\cdot {\rm j}+3\cdot \frac{1 - {\rm j}}{\sqrt{2}}\right)
\Rightarrow \; \; D(1) = \frac{2 + \sqrt{2}}{4} \approx 0.854{\rm V}\hspace{0.05cm}.

Since  D(1)  is purely real,  D(7) = D(1) \; \underline{= 0.854 \ {\rm V}}.

This gives for the corresponding values of the continuous spectral function:

X(f=-f_{\rm A}) = X(f=+f_{\rm A}) =\frac{D(1)}{f_{\rm A}}= 1.708 \cdot 10^{-3}\,{\rm V/Hz}\hspace{0.05cm}.
  • Because of the implicit periodic continuation by the DFT, the value calculated in this way does not exactly match the actual value  (4 \cdot A \cdot T/\pi^2 = 1.621 · 10^{-3}\text{ V/Hz}).
  • The relative error is approx.  5.3\%.