Difference between revisions of "Aufgaben:Exercise 5.5: Fast Fourier Transform"

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{{quiz-Header|Buchseite=*Buch*/*Kapitel*
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{{quiz-Header|Buchseite=Signal_Representation/Fast_Fourier_Transform_(FFT)
 
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[[File:P_ID1177__Sig_A_5_5_neu.png|250px|right|FFT-Algorithmus (Aufgabe A5.5)]]
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[[File:EN_Sig_A_5_5.png|right|frame|FFT algorithm for  $N=8$]]
  
Die Grafik zeigt den Signalflussplan der DFT für N = 8. Aus den Zeitkoeffizienten d(0), ... , d(7) werden die dazugehörigen Spektralkoeffizienten D(0), ... , D(7) ermittelt.
+
The graph shows the signal flow diagram of the Fast Fourier Transform  $\rm (FFT)$  for  $N = 8$.  
Für diese gilt mit 0 ≤ μ ≤ 7:
+
 
 +
The associated spectral coefficients  $D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm} , D(7)$  are determined from the time coefficients  $d(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}, d(7)$.  The following applies to these with  $0 ≤ μ ≤ 7$:
 
   
 
   
$$D(\mu) =  \frac{1}{N}\cdot \sum_{\nu = 0 }^{N-1}
+
:$$D(\mu) =  \frac{1}{N}\cdot \sum_{\nu = 0 }^{N-1}
  d(\nu) \cdot  {w}^{\nu \hspace{0.03cm} \cdot
+
  d(\nu) \cdot  {w}^{\hspace{0.03cm}\nu \hspace{0.05cm} \cdot
 
  \hspace{0.05cm}\mu}\hspace{0.05cm},$$
 
  \hspace{0.05cm}\mu}\hspace{0.05cm},$$
  
wobei der komplexe Drehfaktor w = exp(–j2π/N) zu verwenden ist, also exp(–jπ/4) für N = 8.
+
where the complex rotation factor  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
Am Eingang wird die alternierende ±1–Folge 〈d(ν)〉 angelegt. Nach der Bitumkehroperation ergibt sich daraus die Folge 〈b(κ).
+
\hspace{0.05cm}2\pi /N}$  is to be used, i.e.  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
Es gilt b(κ) = d(ν), wenn man ν als Dualzahl darstellt und die resultierenden 3 Bit als κ in umgekehrter Reihenfolge geschrieben werden. Beispielsweise
+
\hspace{0.05cm}\pi /4}$  für  $N = 8$.
folgt aus ν = 1 (binär 001) die Position κ = 4 (binär 100),
+
 
verbleibt d(2) an der gleichen Position 2 (binär 010).
+
*The alternating $±1$ sequence  $\langle\hspace{0.05cm} d(ν)\hspace{0.05cm}\rangle$  is applied to the input.
Der eigentliche FFT–Algorithmus geschieht für das Beispiel N = 8 in log2 N = 3 Stufen, die mit L = 1, 2 und 3 bezeichnet werden. Weiter gilt:
+
*After the bit reversal operation, this results in the sequence  $\langle \hspace{0.05cm}b(\kappa)\hspace{0.05cm}\rangle$.
In jeder Stufe sind vier Basisoperationen – sog. Butterflies – durchzuführen sind.
+
 
Die Werte am Ausgang der ersten Stufe werden in dieser Aufgabe mit X(0), ... , X(7) bezeichnet, die der zweiten mit Y(0), ... , Y(7).
+
 
Nach der dritten und letzten Stufe sind alle Werte noch durch N zu dividieren.
+
It holds that  $b(κ) = d(ν)$, if  $ν$  is represented as a dual number and the resulting three bits are written as  $κ$  in reverse order.  For example
Hinweis: Die Aufgabe bezieht sich auf den Theorieteil zu Kapitel 5.5.
+
*   $ν = 1$  $($binary  $001)$  is followed by  $κ = 4$  $($binary  $100)$,
 +
*   $d(2)$  remains at the same position  $2$  $($binary  $010)$.
 +
 
 +
 
 +
The actual FFT algorithm happens for the example  $N = 8$  in  $\log_2 N = 3$  stages, denoted  $L = 1$,  $L =2$  and  $L = 3$.  Further:
 +
* In each stage, four basic operations - so-called  '''butterflies'''  - are to be performed.
 +
* The values at the output of the first stage are designated in this task as&nbsp; $X(0),\hspace{0.03cm}\text{...} \hspace{0.1cm} , X(7)$, <br>those of the second as&nbsp; $Y(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}  , Y(7)$.
 +
* After the third and last stage, all values must be divided by&nbsp; $N$.&nbsp; <br>The final result&nbsp; $D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}  , D(7)$&nbsp; is available here.
 +
 
 +
 
 +
 
 +
 
 +
 
 +
 
 +
 
 +
''Hint:''
 +
*This task belongs to the chapter&nbsp; [[Signal_Representation/Fast_Fourier_Transform_(FFT)|Fast Fourier Transform (FFT)]].
 +
 +
 
 +
 
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
  
{Berechnen Sie den DFT–Koeffizienten D(3).
+
{Calculate the DFT coefficient&nbsp; $D(\mu=3)$.
 
|type="{}"}
 
|type="{}"}
$D(3) =$ { 0 }
+
$D(\mu=3) \ = \ $ { 0. }
  
{Berechnen Sie den DFT–Koeffizienten D(4).
+
{Calculate the DFT coefficient&nbsp; $D(\mu=4)$.
 
|type="{}"}
 
|type="{}"}
$D(4) =$ { 1 }
+
$D(\mu=4) \ = \ $ { 1 3% }
  
{Ermitteln Sie die Ausgangswerte X(0), ... , X(7) der ersten Stufe. Welche der folgenden Aussagen sind zutreffend?
+
{Determine the initial values&nbsp; $X(0)$, ... , $X(7)$&nbsp; of the first stage.&nbsp; Which of the following statements are true?
 
|type="[]"}
 
|type="[]"}
- Alle Werte mit geradzahligen Indizes sind gleich 2.
+
- All&nbsp; $X$ values with even indices are equal to&nbsp; $2$.
+ Alle Werte mit ungeradzahligen Indizes sind gleich 0.
+
+ All&nbsp; $X$ values with odd indices are equal to&nbsp; $0$.
 +
 
 +
{Determine the initial values&nbsp; $Y(0)$, ... , $Y(7)$&nbsp; of the second stage.&nbsp; Enter the values&nbsp; $Y(0)$&nbsp; and&nbsp; $Y(4)$&nbsp; as a check.
  
{Ermitteln Sie die Ausgangswerte Y(0), ... , Y(7) der zweiten Stufe. Geben Sie zur Kontrolle die Werte Y(0) und Y(4) ein.
 
 
|type="{}"}
 
|type="{}"}
$Y(0) =$ { 4 }
+
$Y(0) \ = \ $ { 4 3% }
$Y(4) =$ { -4 }
+
$Y(4) \ = \ $ { -4.12--3.88 }
  
{Berechnen Sie alle N Spektralwerte D(μ), insbesondere
+
{Calculate all&nbsp; $N$&nbsp; spectral values&nbsp; $D(\mu)$, in particular
 
|type="{}"}
 
|type="{}"}
$D(\mu = 4) =$ { 4 }
+
$D(\mu =3) \ = \ $ { 0. }
$D(\mu \neq 4) =$ { 0 }
+
$D(\mu = 4) \ = \ $ { 1 3% }
  
{Welche Spektralkoeffizienten würden sich für d(ν = 4) = 1 und d(ν 4) = 0 ergeben? Geben Sie zur Kontrolle die Werte D(3) und D(4) ein:
+
{What would be the spectral coefficients for&nbsp; $d(ν = 4) = 1$&nbsp; and&nbsp; $d(ν \neq 4) = 0$&nbsp;? <br>Enter the values&nbsp; $D(\mu =3)$&nbsp; and&nbsp; $D(\mu =4)$&nbsp; as a check.
 
|type="{}"}
 
|type="{}"}
$D(\mu = 3) =$ { -1 }
+
$D(\mu = 3) \ = \ $ { -1.03--0.97 }
$D(\mu = 4) =$ { 1 }
+
$D(\mu = 4) \ = \ $ { 1 3% }
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
  
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''1.''' a)  Entsprechend der auf dem Angabenblatt gegebenen allgemeinen DFT–Gleichung gilt mit w = exp(–jπ/4) unter Berücksichtigung der alternierenden Zeitkoeffizienten:
+
'''(1)'''&nbsp; According to the general DFT equation given on the specification sheet, with&nbsp; $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
 +
\hspace{0.05cm}\pi /4}$&nbsp; taking into account the alternating time coefficients:
 
   
 
   
$$8 \cdot D(3) & = w^0 - w^3 + w^6- w^9+ w^{12}- w^{15}+ w^{18}-
+
:$$8 \cdot D(3) =   w^0 - w^3 + w^6- w^9+ w^{12}- w^{15}+ w^{18}-
w^{21}= \\ & = &  w^0 - w^3 + w^2- w^1+ w^{4}- w^{7}+ w^{6}-
+
w^{21} =   w^0 - w^3 + w^2- w^1+ w^{4}- w^{7}+ w^{6}-
 
w^{5}\hspace{0.05cm}.$$
 
w^{5}\hspace{0.05cm}.$$
  
Hierbei ist berücksichtigt, dass aufgrund der Periodizität w9 = w1, w12 = w4, w15 = w7, w18 = w2 und w21 = w5 ist. Nach Umsortieren gilt in gleicher Weise
+
*Here it is taken into account that due to the periodicity&nbsp; $w_9 = w_1$,&nbsp; $w_{12} = w_4$,&nbsp; $w_{15} = w_7$,&nbsp; $w_{18} = w_2$&nbsp; und&nbsp; $w_{21} = w_5$&nbsp; ist.  
 +
*After re-sorting, the same applies:
 
   
 
   
$$8 \cdot D(3) & = &   (w^0 + w^4) - (w^1 + w^5)+ (w^2 + w^6) - (w^3 + w^7) = \\
+
:$$8 \cdot D(3) =  (w^0 + w^4) - (w^1 + w^5)+ (w^2 + w^6) - (w^3 + w^7) =  (1 + w + w^2+ w^3) \cdot (w^0 + w^4)\hspace{0.05cm}.$$
& = &   (1 + w + w^2+ w^3) \cdot (w^0 + w^4)\hspace{0.05cm}.$$
+
 
 +
*Thus, because&nbsp; $w_0 = 1$&nbsp; and&nbsp; $w_4 = \text{e}^{-\text{j}\pi } = \hspace{0.08cm} - \hspace{-0.08cm}1$&nbsp;, we obtain&nbsp; $\underline {D(\mu=3) = 0}$.
 +
 
  
Wegen w0 = 1 und w4 = exp(–j · π) = –1 erhält man somit D(3) = 0.
+
'''(2)'''&nbsp; In analogy to sub-taske&nbsp; '''(1)'''&nbsp;, we now get:
b)  In analoger Weise zu a) ergibt sich nun:
 
 
   
 
   
$$8 \cdot D(4) & = w^0 - w^4 + w^8- w^{12}+ w^{16}- w^{20}+
+
:$$ 8 \cdot D(4) =   w^0 - w^4 + w^8- w^{12}+ w^{16}- w^{20}+
w^{24}- w^{28}= \\ & = &  4 \cdot (w^0 - w^4)= 8 \hspace{0.3cm}
+
w^{24}- w^{28}=   4 \cdot (w^0 - w^4)= 8 \hspace{0.3cm}
\Rightarrow \hspace{0.3cm}\hspace{0.15 cm}\underline{D(4) = 1}\hspace{0.05cm}.$$
+
\Rightarrow \hspace{0.3cm}\hspace{0.15 cm}\underline{D(\mu=4) = 1}\hspace{0.05cm}.$$
 +
 
 +
 
 +
[[File:P_ID1178__Sig_A_5_5c_neu.png|right|frame|Example for the FFT algorithm]]
 +
'''(3)'''&nbsp;  <u>Proposed solution 2</u> is correct:
 +
*The term&nbsp; $w^0 = 1$&nbsp; does not have to be taken into account.
 +
*All output values with odd indices are zero by subtracting two identical input values.
 +
*The first statement is not true: &nbsp; It holds&nbsp; $X(0) = X(2) = +2$&nbsp; and&nbsp; $X(4) = X(6) = - 2$.
  
[[File:P_ID1178__Sig_A_5_5c_neu.png|250px|right|Beispiel für den FFT-Algorithmus (ML zu Aufgabe A5.5)]]
 
  
c)  Der Term w0 = 1 muss nicht berücksichtigt werden. Alle Ausgangswerte mit ungeraden Indizes sind somit durch die Subtraktion zweier identischer Eingangswerte gleich 0.
 
Die erste Aussage trifft dagegen nicht zu: Es gilt X(0) = X(2) = +2 und X(4) = X(6) = –2  ⇒  Lösungsvorschlag 2.
 
  
 +
'''(4)'''&nbsp; The multiplication with&nbsp; $w^{2} = -{\rm j}$&nbsp; can be dispensed with, since in the signal flow diagram the corresponding input values are zero.
 +
*One thus obtains&nbsp; $Y(0) \;\underline{= 4}$&nbsp; and&nbsp; $Y(4) \;\underline{=  - \hspace{-0.03cm}4}$.
 +
*All other values are zero.
  
d)  Auf die Multiplikation mit w2 = –j kann verzichtet werden, da im Signalflussplan die entsprechenden Eingangsgrößen 0 sind.
 
Man erhält somit Y(0) = 4 und Y(4) = –4. Alle anderen Werte sind 0.
 
  
  
e) Wegen Y(5) = Y(6) =Y(7) = 0 spielen auch in der dritten Stufe die Multiplikationen mit w, w2 und w3 keine Rolle. Alle Spektralkoeffizienten D(μ) ergeben sich zu 0 mit Ausnahme von
+
'''(5)'''&nbsp; Because of&nbsp; $Y(5) = Y(6) =Y(7) = 0$, the multiplications with&nbsp; $w$,&nbsp; $w^2$&nbsp; and&nbsp; $w^3$&nbsp; do not matter in the third stage either.&nbsp; All spectral coefficients&nbsp; $D(\mu)$&nbsp; therefore result in zero with the exception of
 
   
 
   
$$\hspace{0.15 cm}\underline{D(4)} =  {1}/{N}\cdot \left[Y(0) - Y(4) \right ] \hspace{0.15 cm}\underline{= 1}
+
:$$\hspace{0.15 cm}\underline{D(\mu=4)} =  {1}/{N}\cdot \left[Y(0) - Y(4) \right ] \hspace{0.15 cm}\underline{= 1}
 +
\hspace{0.05cm},$$
 +
:$$\hspace{0.15 cm}\underline{D(\mu=3)} = D(\mu\ne 4)  \hspace{0.15 cm}\underline{= 0}
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
Dieses Ergebnis stimmt mit den Ergebnissen aus a) und b) überein.  
+
This result agrees with the results from&nbsp; '''(1)'''&nbsp; und&nbsp; '''(2)'''.
 +
 
 +
 
 +
 
 +
'''(6)'''&nbsp; Since both the time coefficients&nbsp; $d(ν)$&nbsp; and all spectral coefficients&nbsp; $D(\mu)$&nbsp; are purely real, there is no difference between the FFT and the IFFT.
 +
*This means at the same time:&nbsp; The input and output values can be interchanged.
  
f)  Nachdem sowohl die Zeitkoeffizienten d(ν) als auch alle Spektralkoeffizienten D(μ) rein reell sind, besteht kein Unterschied zwischen der FFT und der IFFT. Das bedeutet gleichzeitig: die Eingangs– und Ausgangswerte können vertauscht werden.
+
*Subtask&nbsp; '''(5)'''&nbsp; gave the following result:
Die Teilaufgabe e) hat das folgende Ergebnis geliefert:
 
 
   
 
   
$$d({\rm gerades}\hspace{0.15cm}\nu) =  +1, \hspace{0.2cm}d({\rm
+
:$$d({\rm even}\hspace{0.15cm}\nu) =  +1, \hspace{0.2cm}d({\rm
ungerades}\hspace{0.15cm}\nu)=  -1 \hspace{0.3cm} \Rightarrow
+
odd}\hspace{0.15cm}\nu)=  -1$$
 +
:$$\Rightarrow
 
\hspace{0.3cm}D(\mu = 4)= 1,\hspace{0.2cm}D(\mu \ne 4)= 0.$$
 
\hspace{0.3cm}D(\mu = 4)= 1,\hspace{0.2cm}D(\mu \ne 4)= 0.$$
  
Durch Vertauschen der Eingangs– und Ausgangswerte kommt man zur Aufgabenstellung von (f):
+
*By swapping the input and output values, we arrive at problem&nbsp; '''(6)''':
 
   
 
   
$$d(\nu = 4)= 1, \hspace{0.2cm}d(\nu \ne 4)= 0 \hspace{0.3cm}
+
:$$d(\nu = 4)= 1, \hspace{0.2cm}d(\nu \ne 4)= 0 \hspace{0.3cm}
 
\Rightarrow \hspace{0.3cm}D({\rm gerades}\hspace{0.15cm}\mu) = +1,
 
\Rightarrow \hspace{0.3cm}D({\rm gerades}\hspace{0.15cm}\mu) = +1,
 
\hspace{0.2cm}D({\rm ungerades}\hspace{0.15cm}\mu)=  -1
 
\hspace{0.2cm}D({\rm ungerades}\hspace{0.15cm}\mu)=  -1
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
Insbesondere würde sich D(3) = –1 und D(4) = +1 ergeben.
+
*In particular, this results in&nbsp; $D(\mu=3) \; \underline{= -1}$&nbsp; und&nbsp; $D(\mu=4) \; \underline{= +1}$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
 
__NOEDITSECTION__
 
__NOEDITSECTION__
[[Category:Aufgaben zu Signaldarstellung|^5. Zeit- und frequenzdisktrete Signaldarstellung^]]
+
[[Category:Signal Representation: Exercises|^5.5 Fast Fourier Transform ^]]

Latest revision as of 17:08, 21 May 2021

FFT algorithm for  $N=8$

The graph shows the signal flow diagram of the Fast Fourier Transform  $\rm (FFT)$  for  $N = 8$.

The associated spectral coefficients  $D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm} , D(7)$  are determined from the time coefficients  $d(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}, d(7)$.  The following applies to these with  $0 ≤ μ ≤ 7$:

$$D(\mu) = \frac{1}{N}\cdot \sum_{\nu = 0 }^{N-1} d(\nu) \cdot {w}^{\hspace{0.03cm}\nu \hspace{0.05cm} \cdot \hspace{0.05cm}\mu}\hspace{0.05cm},$$

where the complex rotation factor  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot \hspace{0.05cm}2\pi /N}$  is to be used, i.e.  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot \hspace{0.05cm}\pi /4}$  für  $N = 8$.

  • The alternating $±1$ sequence  $\langle\hspace{0.05cm} d(ν)\hspace{0.05cm}\rangle$  is applied to the input.
  • After the bit reversal operation, this results in the sequence  $\langle \hspace{0.05cm}b(\kappa)\hspace{0.05cm}\rangle$.


It holds that  $b(κ) = d(ν)$, if  $ν$  is represented as a dual number and the resulting three bits are written as  $κ$  in reverse order.  For example

  •   $ν = 1$  $($binary  $001)$  is followed by  $κ = 4$  $($binary  $100)$,
  •   $d(2)$  remains at the same position  $2$  $($binary  $010)$.


The actual FFT algorithm happens for the example  $N = 8$  in  $\log_2 N = 3$  stages, denoted  $L = 1$,  $L =2$  and  $L = 3$.  Further:

  • In each stage, four basic operations - so-called  butterflies  - are to be performed.
  • The values at the output of the first stage are designated in this task as  $X(0),\hspace{0.03cm}\text{...} \hspace{0.1cm} , X(7)$,
    those of the second as  $Y(0), \hspace{0.03cm}\text{...} \hspace{0.1cm} , Y(7)$.
  • After the third and last stage, all values must be divided by  $N$. 
    The final result  $D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm} , D(7)$  is available here.




Hint:



Questions

1

Calculate the DFT coefficient  $D(\mu=3)$.

$D(\mu=3) \ = \ $

2

Calculate the DFT coefficient  $D(\mu=4)$.

$D(\mu=4) \ = \ $

3

Determine the initial values  $X(0)$, ... , $X(7)$  of the first stage.  Which of the following statements are true?

All  $X$ values with even indices are equal to  $2$.
All  $X$ values with odd indices are equal to  $0$.

4

Determine the initial values  $Y(0)$, ... , $Y(7)$  of the second stage.  Enter the values  $Y(0)$  and  $Y(4)$  as a check.

$Y(0) \ = \ $

$Y(4) \ = \ $

5

Calculate all  $N$  spectral values  $D(\mu)$, in particular

$D(\mu =3) \ = \ $

$D(\mu = 4) \ = \ $

6

What would be the spectral coefficients for  $d(ν = 4) = 1$  and  $d(ν \neq 4) = 0$ ?
Enter the values  $D(\mu =3)$  and  $D(\mu =4)$  as a check.

$D(\mu = 3) \ = \ $

$D(\mu = 4) \ = \ $


Solution

(1)  According to the general DFT equation given on the specification sheet, with  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot \hspace{0.05cm}\pi /4}$  taking into account the alternating time coefficients:

$$8 \cdot D(3) = w^0 - w^3 + w^6- w^9+ w^{12}- w^{15}+ w^{18}- w^{21} = w^0 - w^3 + w^2- w^1+ w^{4}- w^{7}+ w^{6}- w^{5}\hspace{0.05cm}.$$
  • Here it is taken into account that due to the periodicity  $w_9 = w_1$,  $w_{12} = w_4$,  $w_{15} = w_7$,  $w_{18} = w_2$  und  $w_{21} = w_5$  ist.
  • After re-sorting, the same applies:
$$8 \cdot D(3) = (w^0 + w^4) - (w^1 + w^5)+ (w^2 + w^6) - (w^3 + w^7) = (1 + w + w^2+ w^3) \cdot (w^0 + w^4)\hspace{0.05cm}.$$
  • Thus, because  $w_0 = 1$  and  $w_4 = \text{e}^{-\text{j}\pi } = \hspace{0.08cm} - \hspace{-0.08cm}1$ , we obtain  $\underline {D(\mu=3) = 0}$.


(2)  In analogy to sub-taske  (1) , we now get:

$$ 8 \cdot D(4) = w^0 - w^4 + w^8- w^{12}+ w^{16}- w^{20}+ w^{24}- w^{28}= 4 \cdot (w^0 - w^4)= 8 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}\hspace{0.15 cm}\underline{D(\mu=4) = 1}\hspace{0.05cm}.$$


Example for the FFT algorithm

(3)  Proposed solution 2 is correct:

  • The term  $w^0 = 1$  does not have to be taken into account.
  • All output values with odd indices are zero by subtracting two identical input values.
  • The first statement is not true:   It holds  $X(0) = X(2) = +2$  and  $X(4) = X(6) = - 2$.


(4)  The multiplication with  $w^{2} = -{\rm j}$  can be dispensed with, since in the signal flow diagram the corresponding input values are zero.

  • One thus obtains  $Y(0) \;\underline{= 4}$  and  $Y(4) \;\underline{= - \hspace{-0.03cm}4}$.
  • All other values are zero.


(5)  Because of  $Y(5) = Y(6) =Y(7) = 0$, the multiplications with  $w$,  $w^2$  and  $w^3$  do not matter in the third stage either.  All spectral coefficients  $D(\mu)$  therefore result in zero with the exception of

$$\hspace{0.15 cm}\underline{D(\mu=4)} = {1}/{N}\cdot \left[Y(0) - Y(4) \right ] \hspace{0.15 cm}\underline{= 1} \hspace{0.05cm},$$
$$\hspace{0.15 cm}\underline{D(\mu=3)} = D(\mu\ne 4) \hspace{0.15 cm}\underline{= 0} \hspace{0.05cm}.$$

This result agrees with the results from  (1)  und  (2).


(6)  Since both the time coefficients  $d(ν)$  and all spectral coefficients  $D(\mu)$  are purely real, there is no difference between the FFT and the IFFT.

  • This means at the same time:  The input and output values can be interchanged.
  • Subtask  (5)  gave the following result:
$$d({\rm even}\hspace{0.15cm}\nu) = +1, \hspace{0.2cm}d({\rm odd}\hspace{0.15cm}\nu)= -1$$
$$\Rightarrow \hspace{0.3cm}D(\mu = 4)= 1,\hspace{0.2cm}D(\mu \ne 4)= 0.$$
  • By swapping the input and output values, we arrive at problem  (6):
$$d(\nu = 4)= 1, \hspace{0.2cm}d(\nu \ne 4)= 0 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}D({\rm gerades}\hspace{0.15cm}\mu) = +1, \hspace{0.2cm}D({\rm ungerades}\hspace{0.15cm}\mu)= -1 \hspace{0.05cm}.$$
  • In particular, this results in  $D(\mu=3) \; \underline{= -1}$  und  $D(\mu=4) \; \underline{= +1}$.