Difference between revisions of "Aufgaben:Exercise 5.2: Inverse Discrete Fourier Transform"

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[[File:P_ID1138__Sig_A_5_2.png|250px|right|frame|Fünf verschiedene Sätze für die Spektralkoeffizienten  $D(\mu)$]]
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[[File:P_ID1138__Sig_A_5_2.png|250px|right|frame|Five different sets for the spectral coefficients  $D(\mu)$]]
  
Bei der ''Diskreten Fouriertransformation''  (DFT) werden
+
With the ''Discrete Fourier Transform''  (DFT), the following are obtained
*aus den  $N$  Zeitkoeffizienten  $d(\nu)$   ⇒    Abtastwerte des zeitkontinuierlichen Signals  $x(t)$ –  
+
*from the  $N$  time coefficients  $d(\nu)$   ⇒    samples of the continuous-time signal  $x(t)$ –  
*die  $N$  Spektralbereichskoeffizienten  $D(\mu)$  
+
*the  $N$  spectral range coefficients  $D(\mu)$  
  
  
berechnet. Mit  $\nu = 0$, ... , $N – 1$  und  $\mu = 0$, ... , $N – 1$  gilt:
+
are calculated. With  $\nu = 0$, ... , $N – 1$  and  $\mu = 0$, ... , $N – 1$  holds:
 
   
 
   
 
:$$D(\mu) = \frac{1}{N} \cdot \sum_{\nu = 0 }^{N-1}
 
:$$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}.$$
 
   d(\nu)\cdot  {w}^{\hspace{0.05cm}\nu \hspace{0.05cm} \cdot \hspace{0.05cm}\mu} \hspace{0.05cm}.$$
  
Hierbei bezeichnet  $w$  den komplexen Drehfaktor:
+
Here  $w$  denotes the complex rotation factor:
 
   
 
   
 
:$$w  = {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} 2 \pi /N}
 
:$$w  = {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} 2 \pi /N}
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  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Für die ''Inverse Diskrete Fouriertransformation''  (IDFT)    ⇒    „Umkehrfunktion” der DFT gilt entsprechend:
+
For the ''Inverse Discrete Fourier Transform''  (IDFT)    ⇒    „inverse function” of the DFT, the following applies accordingly:
 +
 
 
   
 
   
 
:$$d(\nu) =  \sum_{\mu = 0 }^{N-1}
 
:$$d(\nu) =  \sum_{\mu = 0 }^{N-1}
 
  D(\mu) \cdot  {w}^{-\nu \hspace{0.05cm} \cdot \hspace{0.05cm}\mu} \hspace{0.05cm}.$$
 
  D(\mu) \cdot  {w}^{-\nu \hspace{0.05cm} \cdot \hspace{0.05cm}\mu} \hspace{0.05cm}.$$
  
In dieser Aufgabe sollen für verschiedene Beispielfolgen  $D(\mu)$  (die in der obigen Tabelle mit  $\rm A$, ... ,  $\rm E$ bezeichnet sind) die Zeitkoeffizienten  $d(\nu)$  ermittelt werden. Es gilt somit stets  $N = 8$.
+
In this task, the time coefficients  $d(\nu)$  are to be determined for various example sequences (which are labelled  $\rm A$, ... ,  $\rm E$ in the table above)  $D(\mu)$  ermittelt werden. Thus,  $N = 8$ always applies.
  
  
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''Hinweise:''  
+
''Hints:''  
*Die Aufgabe gehört zum  Kapitel  [[Signal_Representation/Discrete_Fourier_Transform_(DFT)|Diskrete Fouriertransformation (DFT)]].
+
*This task belongs to the chapter  [[Signal_Representation/Discrete_Fourier_Transform_(DFT)|Discrete Fourier Transformation (DFT)]].
 
   
 
   
*Die hier behandelte Thematik wird auch im interaktiven Applet  [[Applets:Diskrete_Fouriertransformation_und_Inverse|Diskrete Fouriertransformation und Inverse]] behandelt.
+
*The topic dealt with here is also dealt with in the interactive applet  [[Applets:Diskrete_Fouriertransformation_und_Inverse|Discrete Fourier Transform and Inverse]].
  
  
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Wie lauten die Zeitkoeffizienten&nbsp; $d(\nu)$&nbsp; für die&nbsp; $D(\mu)$–Werte von Spalte&nbsp; $\rm A$?
+
{What are the time coefficients&nbsp; $d(\nu)$&nbsp; for the&nbsp; $D(\mu)$–values of column&nbsp; $\rm A$?
 
|type="{}"}
 
|type="{}"}
 
$d(0)\ = \ $  { 1 3% }
 
$d(0)\ = \ $  { 1 3% }
 
$d(1)\ = \ $ { 1 3% }
 
$d(1)\ = \ $ { 1 3% }
  
{Wie lauten die Zeitkoeffizienten&nbsp; $d(ν)$&nbsp; für die&nbsp; $D(\mu)$–Werte von Spalte&nbsp; $\rm B$?
+
{What are the time coefficients&nbsp; $d(ν)$&nbsp; for the&nbsp; $D(\mu)$–values of column&nbsp; $\rm B$?
 
|type="{}"}
 
|type="{}"}
 
$d(0)\ = \ $ { 1 3% }
 
$d(0)\ = \ $ { 1 3% }
 
$d(1)\ = \ $ { 0.707 3% }
 
$d(1)\ = \ $ { 0.707 3% }
  
{Wie lauten die Zeitkoeffizienten&nbsp; $d(ν)$&nbsp; für die&nbsp; $D(\mu)$–Werte von Spalte&nbsp; $\rm C$?
+
{What are the time coefficients&nbsp; $d(ν)$&nbsp; for the&nbsp; $D(\mu)$–values of column&nbsp; $\rm C$?
 
|type="{}"}
 
|type="{}"}
 
$d(0)\ = \ $ { 1 3% }
 
$d(0)\ = \ $ { 1 3% }
 
$d(1)\ = \ $ { 0. }
 
$d(1)\ = \ $ { 0. }
  
{Wie lauten die Zeitkoeffizienten&nbsp; $d(ν)$&nbsp; für die&nbsp; $D(\mu)$–Werte von Spalte&nbsp; $\rm D$?
+
{What are the time coefficients&nbsp; $d(ν)$&nbsp; for the&nbsp; $D(\mu)$–values of column&nbsp; $\rm D$?
 
|type="{}"}
 
|type="{}"}
 
$d(0)\ = \ ${ 1 3% }
 
$d(0)\ = \ ${ 1 3% }
 
$d(1)\ = \ $ { -1.03--0.97 }
 
$d(1)\ = \ $ { -1.03--0.97 }
  
{Wie lauten die Zeitkoeffizienten&nbsp; $d(ν)$&nbsp; für die&nbsp; $D(\mu)$–Werte von Spalte&nbsp; $\rm E$?
+
{What are the time coefficients&nbsp; $d(ν)$&nbsp; for the&nbsp; $D(\mu)$–values of column&nbsp; $\rm E$?
 
|type="{}"}
 
|type="{}"}
 
$d(0)\ = \ $ { 2 3% }
 
$d(0)\ = \ $ { 2 3% }
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</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Aus der IDFT–Gleichung wird mit&nbsp; $D(\mu) = 0$&nbsp; für&nbsp; $\mu \ne 0$:
+
'''(1)'''&nbsp; From the IDFT equation, with&nbsp; $D(\mu) = 0$&nbsp; for&nbsp; $\mu \ne 0$:
 
    
 
    
 
:$$d(\nu) = D(0) \cdot w^0 = D(0) =1\hspace{0.5cm}(0 \le \nu \le 7)\ \hspace{0.5cm} \Rightarrow\hspace{0.5cm}\hspace{0.15 cm}\underline{d(0) = d(1) = 1}.$$
 
:$$d(\nu) = D(0) \cdot w^0 = D(0) =1\hspace{0.5cm}(0 \le \nu \le 7)\ \hspace{0.5cm} \Rightarrow\hspace{0.5cm}\hspace{0.15 cm}\underline{d(0) = d(1) = 1}.$$
  
*Dieser Parametersatz beschreibt die diskrete Form der Fourierkorrespondenz des Gleichsignals:
+
*This set of parameters describes the discrete form of the Fourier correspondence of the DC signal:
 
   
 
   
 
:$$x(t) = 1 \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
 
:$$x(t) = 1 \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
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'''(2)'''&nbsp; Alle Spektralkoeffizienten sind Null mit Ausnahme von&nbsp; $D_1 = D_7 = 0.5$. Daraus folgt für&nbsp; $0 ≤ ν ≤ 7$:
+
'''(2)'''&nbsp; All spectral coefficients are zero except&nbsp; $D_1 = D_7 = 0.5$. It follows for&nbsp; $0 ≤ ν ≤ 7$:
 
   
 
   
 
:$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu}
 
:$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu}
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Aufgrund der Periodizität gilt aber auch:
+
*However, due to periodicity, also holds:
 
   
 
   
 
:$$d(\nu)  =  0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{4} \cdot \nu \right)  \hspace{0.3cm} \Rightarrow  \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) = {1}/{\sqrt{2}} \approx 0.707}
 
:$$d(\nu)  =  0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{4} \cdot \nu \right)  \hspace{0.3cm} \Rightarrow  \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) = {1}/{\sqrt{2}} \approx 0.707}
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Es handelt sich also um das zeitdiskrete Äquivalent zu
+
*It is therefore the discrete-time equivalent of
 
   
 
   
 
:$$x(t) = \cos(2 \pi \cdot f_{\rm A} \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
 
:$$x(t) = \cos(2 \pi \cdot f_{\rm A} \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
 
  X(f) =  {1}/{2} \cdot {\delta}(f + f_{\rm A}) +  {1}/{2} \cdot {\delta}(f - f_{\rm A}) \hspace{0.05cm},$$
 
  X(f) =  {1}/{2} \cdot {\delta}(f + f_{\rm A}) +  {1}/{2} \cdot {\delta}(f - f_{\rm A}) \hspace{0.05cm},$$
  
:wobei&nbsp; $f_{\rm A}$&nbsp; die kleinste in der DFT darstellbare Frequenz bezeichnet.
+
:where&nbsp; $f_{\rm A}$&nbsp; denotes the smallest frequency that can be represented in the DFT.
  
  
'''(3)'''&nbsp; Gegenüber der Teilaufgabe&nbsp; '''(2)'''&nbsp; ist nun die Schwingungsfrequenz doppelt so groß, nämlich&nbsp; $2 f_{\rm A}$&nbsp; anstelle von&nbsp; $f_{\rm A}$:
+
'''(3)'''&nbsp; Compared to subtask&nbsp; '''(2)'''&nbsp;, the oscillation frequency is now twice as large, namely&nbsp; $2 f_{\rm A}$&nbsp; instead of&nbsp; $f_{\rm A}$:
 
   
 
   
 
:$$x(t) = \cos(2 \pi \cdot (2f_{\rm A}) \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
 
:$$x(t) = \cos(2 \pi \cdot (2f_{\rm A}) \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm}
 
  X(f) = {1}/{2} \cdot {\delta}(f + 2f_{\rm A}) + {1}/{2} \cdot {\delta}(f - 2f_{\rm A}) \hspace{0.05cm},$$
 
  X(f) = {1}/{2} \cdot {\delta}(f + 2f_{\rm A}) + {1}/{2} \cdot {\delta}(f - 2f_{\rm A}) \hspace{0.05cm},$$
  
*Damit beschreibt die Folge&nbsp;  $\langle \hspace{0.1cm}d(ν)\hspace{0.1cm}\rangle $&nbsp; zwei Perioden der Cosinusschwingung, und es gilt für&nbsp; $0 ≤ ν ≤ 7$:
+
*Thus the sequence&nbsp;  $\langle \hspace{0.1cm}d(ν)\hspace{0.1cm}\rangle $&nbsp; describes two periods of the cosine oscillation, and it holds for&nbsp; $0 ≤ ν ≤ 7$:
 
   
 
   
 
:$$ d(\nu)  =  0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{2} \cdot \nu \right)\hspace{0.3cm}  \Rightarrow  \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1, \hspace{0.2cm}d(1) = 0}
 
:$$ d(\nu)  =  0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{2} \cdot \nu \right)\hspace{0.3cm}  \Rightarrow  \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1, \hspace{0.2cm}d(1) = 0}
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'''(4)'''&nbsp; Durch eine weitere Verdoppelung der Cosinusfrequenz auf&nbsp; $4 f_{\rm A}$&nbsp; kommt man schließlich zur zeitkontinuierlichen Fourierkorrespondenz
+
'''(4)'''&nbsp; By further doubling the cosine frequency to&nbsp; $4 f_{\rm A}$&nbsp; one finally arrives at the continuous-time Fourier correspondence
 
   
 
   
 
:$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi  \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi  \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left(\pi \cdot \nu \right)
 
:$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi  \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi  \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left(\pi \cdot \nu \right)
 
  \hspace{0.05cm}$$
 
  \hspace{0.05cm}$$
  
:und damit zu den Zeitkoeffizienten
+
:and thus to the time coefficients
 
   
 
   
 
:$$d(0) =d(2) =d(4) =d(6) \hspace{0.15 cm}\underline{= +1}, \hspace{0.2cm}d(1) =d(3) =d(5) =d(7)  \hspace{0.15 cm}\underline{= -1}
 
:$$d(0) =d(2) =d(4) =d(6) \hspace{0.15 cm}\underline{= +1}, \hspace{0.2cm}d(1) =d(3) =d(5) =d(7)  \hspace{0.15 cm}\underline{= -1}
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Zu beachten ist, dass hier die beiden Diracfunktionen in der zeitdiskreten Darstellung aufgrund der Periodizität zusammenfallen.
+
*Note that here the two Dirac functions coincide in the discrete-time representation due to periodicity.
*Die Koeffizienten&nbsp; $D (+4) = 0.5$&nbsp; und&nbsp; $D (-4) = 0.5$&nbsp; ergeben zusammen&nbsp; $D (4) = 1$.
+
*The coefficients&nbsp; $D (+4) = 0.5$&nbsp; and&nbsp; $D (-4) = 0.5$&nbsp; together give&nbsp; $D (4) = 1$.
  
  
  
'''(5)'''&nbsp; Die Diskrete Fouriertransformation ist ebenfalls linear. Deshalb ist das Superpositionsprinzip weiterhin anwendbar:  
+
'''(5)'''&nbsp; The Discrete Fourier Transform is also linear. Therefore, the superposition principle is still applicable:  
*Die Koeffizienten&nbsp; $D(\mu )$&nbsp; aus Spalte&nbsp; $\rm E$&nbsp; ergeben sich als die Summen der Spalten&nbsp; $\rm A$&nbsp; und&nbsp; $\rm D$.  
+
*The coefficients&nbsp; $D(\mu )$&nbsp; from column&nbsp; $\rm E$&nbsp; result as the sums of columns&nbsp; $\rm A$&nbsp; and&nbsp; $\rm D$.  
*Deshalb wird aus der alternierenden Folge&nbsp;  $\langle \hspace{0.1cm}d(ν) \hspace{0.1cm}\rangle $&nbsp; entsprechend Teilaufgabe&nbsp; '''(4)'''&nbsp; die um&nbsp; $1$&nbsp; nach oben verschobene Folge:
+
*Therefore, the alternating sequence&nbsp;  $\langle \hspace{0.1cm}d(ν) \hspace{0.1cm}\rangle $&nbsp; becomes the sequence shifted up by&nbsp; $1$&nbsp; according to subtask&nbsp; '''(4)'''&nbsp;:
 
   
 
   
 
:$$ \hspace{0.15 cm}\underline{d(0) =d(2) =d(4) =d(6)= 2}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) =d(3) =d(5) =d(7)  = 0}
 
:$$ \hspace{0.15 cm}\underline{d(0) =d(2) =d(4) =d(6)= 2}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) =d(3) =d(5) =d(7)  = 0}

Revision as of 21:01, 20 March 2021

Five different sets for the spectral coefficients  $D(\mu)$

With the Discrete Fourier Transform  (DFT), the following are obtained

  • from the  $N$  time coefficients  $d(\nu)$   ⇒   samples of the continuous-time signal  $x(t)$ –
  • the  $N$  spectral range coefficients  $D(\mu)$


are calculated. With  $\nu = 0$, ... , $N – 1$  and  $\mu = 0$, ... , $N – 1$  holds:

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

Here  $w$  denotes the complex rotation factor:

$$w = {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} 2 \pi /N} = \cos \left( {2 \pi}/{N}\right)-{\rm j} \cdot \sin \left( {2 \pi}/{N}\right) \hspace{0.05cm}.$$

For the Inverse Discrete Fourier Transform  (IDFT)   ⇒   „inverse function” of the DFT, the following applies accordingly:


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

In this task, the time coefficients  $d(\nu)$  are to be determined for various example sequences (which are labelled  $\rm A$, ... ,  $\rm E$ in the table above)  $D(\mu)$  ermittelt werden. Thus,  $N = 8$ always applies.





Hints:


Questions

1

What are the time coefficients  $d(\nu)$  for the  $D(\mu)$–values of column  $\rm A$?

$d(0)\ = \ $

$d(1)\ = \ $

2

What are the time coefficients  $d(ν)$  for the  $D(\mu)$–values of column  $\rm B$?

$d(0)\ = \ $

$d(1)\ = \ $

3

What are the time coefficients  $d(ν)$  for the  $D(\mu)$–values of column  $\rm C$?

$d(0)\ = \ $

$d(1)\ = \ $

4

What are the time coefficients  $d(ν)$  for the  $D(\mu)$–values of column  $\rm D$?

$d(0)\ = \ $

$d(1)\ = \ $

5

What are the time coefficients  $d(ν)$  for the  $D(\mu)$–values of column  $\rm E$?

$d(0)\ = \ $

$d(1)\ = \ $


Solution

(1)  From the IDFT equation, with  $D(\mu) = 0$  for  $\mu \ne 0$:

$$d(\nu) = D(0) \cdot w^0 = D(0) =1\hspace{0.5cm}(0 \le \nu \le 7)\ \hspace{0.5cm} \Rightarrow\hspace{0.5cm}\hspace{0.15 cm}\underline{d(0) = d(1) = 1}.$$
  • This set of parameters describes the discrete form of the Fourier correspondence of the DC signal:
$$x(t) = 1 \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm} X(f) = {\delta}(f) \hspace{0.05cm}.$$


(2)  All spectral coefficients are zero except  $D_1 = D_7 = 0.5$. It follows for  $0 ≤ ν ≤ 7$:

$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} \hspace{0.05cm}.$$
  • However, due to periodicity, also holds:
$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /4) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{4} \cdot \nu \right) \hspace{0.3cm} \Rightarrow \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) = {1}/{\sqrt{2}} \approx 0.707} \hspace{0.05cm}.$$
  • It is therefore the discrete-time equivalent of
$$x(t) = \cos(2 \pi \cdot f_{\rm A} \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm} X(f) = {1}/{2} \cdot {\delta}(f + f_{\rm A}) + {1}/{2} \cdot {\delta}(f - f_{\rm A}) \hspace{0.05cm},$$
where  $f_{\rm A}$  denotes the smallest frequency that can be represented in the DFT.


(3)  Compared to subtask  (2) , the oscillation frequency is now twice as large, namely  $2 f_{\rm A}$  instead of  $f_{\rm A}$:

$$x(t) = \cos(2 \pi \cdot (2f_{\rm A}) \cdot t) \hspace{0.2cm}\circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.2cm} X(f) = {1}/{2} \cdot {\delta}(f + 2f_{\rm A}) + {1}/{2} \cdot {\delta}(f - 2f_{\rm A}) \hspace{0.05cm},$$
  • Thus the sequence  $\langle \hspace{0.1cm}d(ν)\hspace{0.1cm}\rangle $  describes two periods of the cosine oscillation, and it holds for  $0 ≤ ν ≤ 7$:
$$ d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} (\pi /2) \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left({\pi}/{2} \cdot \nu \right)\hspace{0.3cm} \Rightarrow \hspace{0.3cm}\hspace{0.15 cm}\underline{d(0) = 1, \hspace{0.2cm}d(1) = 0} \hspace{0.05cm}.$$


(4)  By further doubling the cosine frequency to  $4 f_{\rm A}$  one finally arrives at the continuous-time Fourier correspondence

$$d(\nu) = 0.5 \cdot {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} + 0.5 \cdot {\rm e}^{{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} \pi \hspace{0.05cm}\cdot \hspace{0.05cm} \nu} = \cos \left(\pi \cdot \nu \right) \hspace{0.05cm}$$
and thus to the time coefficients
$$d(0) =d(2) =d(4) =d(6) \hspace{0.15 cm}\underline{= +1}, \hspace{0.2cm}d(1) =d(3) =d(5) =d(7) \hspace{0.15 cm}\underline{= -1} \hspace{0.05cm}.$$
  • Note that here the two Dirac functions coincide in the discrete-time representation due to periodicity.
  • The coefficients  $D (+4) = 0.5$  and  $D (-4) = 0.5$  together give  $D (4) = 1$.


(5)  The Discrete Fourier Transform is also linear. Therefore, the superposition principle is still applicable:

  • The coefficients  $D(\mu )$  from column  $\rm E$  result as the sums of columns  $\rm A$  and  $\rm D$.
  • Therefore, the alternating sequence  $\langle \hspace{0.1cm}d(ν) \hspace{0.1cm}\rangle $  becomes the sequence shifted up by  $1$  according to subtask  (4) :
$$ \hspace{0.15 cm}\underline{d(0) =d(2) =d(4) =d(6)= 2}, \hspace{0.2cm}\hspace{0.15 cm}\underline{d(1) =d(3) =d(5) =d(7) = 0} \hspace{0.05cm}.$$