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

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[[File:EN_Sig_A_5_5.png|right|frame|FFT-Algorithmus für  N=8]]
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[[File:EN_Sig_A_5_5.png|right|frame|FFT algorithm for  N=8]]
  
Die Grafik zeigt den Signalflussplan der FFT für  N=8. Aus den Zeitkoeffizienten  $d(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}, d(7)$  werden die dazugehörigen Spektralkoeffizienten  $D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm} , D(7)$  ermittelt. Für diese gilt mit  0 ≤ μ ≤ 7:
+
The graph shows the signal flow diagram of the 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}
 
:$$D(\mu) =  \frac{1}{N}\cdot \sum_{\nu = 0 }^{N-1}
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  \hspace{0.05cm}\mu}\hspace{0.05cm},$$
 
  \hspace{0.05cm}\mu}\hspace{0.05cm},$$
  
wobei der komplexe Drehfaktor  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
+
where the complex rotation factor  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
  \hspace{0.05cm}2\pi /N}$  zu verwenden ist, also  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
+
  \hspace{0.05cm}2\pi /N}$  is to be used, i.e.  $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
 
  \hspace{0.05cm}\pi /4}  für  N = 8$.
 
  \hspace{0.05cm}\pi /4}  für  N = 8$.
  
*Am Eingang wird die alternierende ±1–Folge  \langle\hspace{0.05cm} d(ν)\hspace{0.05cm}\rangle  angelegt.  
+
*The alternating ±1 sequence  \langle\hspace{0.05cm} d(ν)\hspace{0.05cm}\rangle  is applied to the input.
*Nach der Bitumkehroperation ergibt sich daraus die Folge  \langle \hspace{0.05cm}b(\kappa)\hspace{0.05cm}\rangle.
+
*After the bit reversal operation, this results in the sequence  \langle \hspace{0.05cm}b(\kappa)\hspace{0.05cm}\rangle.
  
  
Es gilt  b(κ) = d(ν), wenn man  ν  als Dualzahl darstellt und die resultierenden drei Bit als  κ  in umgekehrter Reihenfolge geschrieben werden. Beispielsweise
+
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
* folgt aus  ν = 1  (binär  001)  die Position  κ = 4  (binär  100),
+
*   ν = 1  (binary  001)  is followed by  κ = 4  (binary  100),
* verbleibt  d(2)  an der gleichen Position  2  (binär  010).
+
*   d(2)  remains at the same position  2  (binary  010).
  
  
Der eigentliche FFT–Algorithmus geschieht für das Beispiel  N = 8  in  \log_2 N = 3  Stufen, die mit  L = 1,  L =2  und  L = 3  bezeichnet werden. Weiter gilt:
+
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 jeder Stufe sind vier Basisoperationen – so genannte ''Butterflies'' – durchzuführen.
+
* In each stage, four basic operations - so-called ''butterflies'' - are to be performed.
* Die Werte am Ausgang der ersten Stufe werden in dieser Aufgabe mit  X(0),\hspace{0.03cm}\text{...} \hspace{0.1cm} , X(7)  bezeichnet, die der zweiten mit  Y(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}  , Y(7).
+
* 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).
* Nach der dritten und letzten Stufe sind alle Werte noch durch  N  zu dividieren. Hier liegt dann das endgültige Ergebnis  D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}  , D(7)  vor.
+
* 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 then available here.
  
  
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''Hinweis:''  
+
''Hint:''  
*Die Aufgabe gehört zum  Kapitel  [[Signal_Representation/Fast_Fourier_Transform_(FFT)|Fast-Fouriertransformation (FFT)]].
+
*This task belongs to the chapter  [[Signal_Representation/Fast_Fourier_Transform_(FFT)|Fast Fourier Transform (FFT)]].
 
   
 
   
  
  
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
  
{Berechnen Sie den DFT–Koeffizienten&nbsp; D(3).
+
{Calculate the DFT coefficient&nbsp; D(3).
 
|type="{}"}
 
|type="{}"}
 
D(3) \ = \ { 0. }
 
D(3) \ = \ { 0. }
  
{Berechnen Sie den DFT–Koeffizienten&nbsp; D(4).
+
{Calculate the DFT coefficient&nbsp; D(4).
 
|type="{}"}
 
|type="{}"}
 
D(4) \ = \ { 1 3% }
 
D(4) \ = \ { 1 3% }
  
{Ermitteln Sie die Ausgangswerte&nbsp; X(0), ... , X(7)&nbsp; der ersten Stufe. Welche der folgenden Aussagen sind zutreffend?
+
{Determine the initial values&nbsp; X(0), ... , X(7)&nbsp; of the first stage. Which of the following statements are true?
 
|type="[]"}
 
|type="[]"}
- Alle&nbsp; X&ndash;Werte mit geradzahligen Indizes sind gleich&nbsp; 2.
+
- All&nbsp; X&ndash;values with even indices are equal to&nbsp; 2.
+ Alle&nbsp; X&ndash;Werte mit ungeradzahligen Indizes sind gleich&nbsp; 0.
+
+ All&nbsp; X&ndash;values with odd indices are equal to&nbsp; 0.
 +
 
 +
{Determine the initial values&nbsp; Y(0), ... , Y(7)&nbsp; of the second stage. Enter the values&nbsp; Y(0)&nbsp; and&nbsp; Y(4)&nbsp; as a check.
  
{Ermitteln Sie die Ausgangswerte&nbsp; Y(0), ... , Y(7)&nbsp; der zweiten Stufe. Geben Sie zur Kontrolle die Werte&nbsp; Y(0)&nbsp; und&nbsp; Y(4)&nbsp; ein.
 
 
|type="{}"}
 
|type="{}"}
 
Y(0) \ = \ { 4 3% }
 
Y(0) \ = \ { 4 3% }
 
Y(4) \ = \ { -4.12--3.88 }
 
Y(4) \ = \ { -4.12--3.88 }
  
{Berechnen Sie alle&nbsp; N&nbsp; Spektralwerte&nbsp; D(\mu), insbesondere
+
{Calculate all&nbsp; N&nbsp; spectral values&nbsp; D(\mu), in particular
 
|type="{}"}
 
|type="{}"}
 
D(\mu = 4) \ = \ { 1 3% }
 
D(\mu = 4) \ = \ { 1 3% }
 
D(\mu \neq 4) \ = \ { 0. }
 
D(\mu \neq 4) \ = \ { 0. }
  
{Welche Spektralkoeffizienten würden sich für&nbsp; d(ν = 4) = 1&nbsp; und&nbsp; d(ν \neq 4) = 0&nbsp; ergeben? <br>Geben Sie zur Kontrolle die Werte&nbsp; D(3)&nbsp; und&nbsp; D(4)&nbsp; 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(3)&nbsp; and&nbsp; D(4)&nbsp; as a check.
 
|type="{}"}
 
|type="{}"}
 
D(\mu = 3) \ = \ { -1.03--0.97 }
 
D(\mu = 3) \ = \ { -1.03--0.97 }
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</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
  
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Entsprechend der auf dem Angabenblatt gegebenen allgemeinen DFT–Gleichung gilt mit&nbsp; $w = \text{e}^{-\text{j}\hspace{0.05cm} \cdot
+
'''(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; unter Berücksichtigung der alternierenden Zeitkoeffizienten:
+
  \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}-
 
:$$8 \cdot D(3)  =    w^0 - w^3 + w^6- w^9+ w^{12}- w^{15}+ w^{18}-
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w^{5}\hspace{0.05cm}.$$
 
w^{5}\hspace{0.05cm}.$$
  
*Hierbei ist berücksichtigt, dass aufgrund der Periodizität&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.  
+
*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.  
*Nach Umsortieren gilt in gleicher Weise:
+
*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}.
 
: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}.
  
*Wegen&nbsp; w_0 = 1&nbsp; und&nbsp; w_4 = \text{e}^{-\text{j}\pi } = \hspace{0.08cm} - \hspace{-0.08cm}1&nbsp; erhält man somit&nbsp; \underline {D(3) = 0}.
+
*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(3) = 0}.
  
  
'''(2)'''&nbsp; In analoger Weise zur Teilaufgabe&nbsp; '''(1)'''&nbsp; ergibt sich nun:
+
'''(2)'''&nbsp; In analogy to sub-taske&nbsp; '''(1)'''&nbsp;, we now get:
 
   
 
   
 
:$$ 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}+
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[[File:P_ID1178__Sig_A_5_5c_neu.png|right|frame|Beispiel für den FFT-Algorithmus]]
+
[[File:P_ID1178__Sig_A_5_5c_neu.png|right|frame|Example for the FFT algorithm]]
'''(3)'''&nbsp; Richtig ist der <u>Lösungsvorschlag 2</u>:
+
'''(3)'''&nbsp; <u>Proposed solution 2</u> is correct:
*Der Term&nbsp; w^0 = 1&nbsp; muss nicht berücksichtigt werden.  
+
*The term&nbsp; w^0 = 1&nbsp; does not have to be taken into account.
*Alle Ausgangswerte mit ungeraden Indizes sind durch die Subtraktion zweier identischer Eingangswerte Null.  
+
*All output values with odd indices are zero by subtracting two identical input values.
*Die erste Aussage trifft nicht zu: &nbsp; Es gilt&nbsp; X(0) = X(2) = +2&nbsp; und&nbsp; X(4) = X(6) = - 2.  
+
*The first statement is not true: &nbsp; Es gilt&nbsp; X(0) = X(2) = +2&nbsp; and&nbsp; X(4) = X(6) = - 2.  
  
  
  
'''(4)'''&nbsp; Auf die Multiplikation mit&nbsp; w^{2} = -{\rm j}&nbsp; kann verzichtet werden, da im Signalflussplan die entsprechenden Eingangsgrößen Null sind.
+
'''(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.
*Man erhält somit&nbsp; Y(0) \;\underline{= 4}&nbsp; und&nbsp; Y(4) \;\underline{=  - \hspace{-0.03cm}4}.  
+
*One thus obtains&nbsp; Y(0) \;\underline{= 4}&nbsp; and&nbsp; Y(4) \;\underline{=  - \hspace{-0.03cm}4}.  
*Alle anderen Werte sind Null.  
+
*All other values are zero.
  
  
  
'''(5)'''&nbsp; Wegen&nbsp; Y(5) = Y(6) =Y(7) = 0&nbsp; spielen auch in der dritten Stufe die Multiplikationen mit&nbsp; w,&nbsp; w^2&nbsp; und&nbsp; w^3&nbsp; keine Rolle. Alle Spektralkoeffizienten&nbsp; D(\mu)&nbsp; ergeben sich deshalb zu Null mit Ausnahme von
+
'''(5)'''&nbsp; Because of&nbsp; Y(5) = Y(6) =Y(7) = 0&nbsp; , the multiplications with&nbsp; w,&nbsp; w^2&nbsp; and&nbsp; w^3&nbsp; do not matter in the third stage either. 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(4)} =  {1}/{N}\cdot \left[Y(0) - Y(4) \right ] \hspace{0.15 cm}\underline{= 1}
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
Dieses Ergebnis stimmt mit den Ergebnissen aus&nbsp; '''(1)'''&nbsp; und&nbsp; '''(2)'''&nbsp; überein.  
+
This result agrees with the results from&nbsp; '''(1)'''&nbsp; und&nbsp; '''(2)'''&nbsp;.
  
  
  
'''(6)'''&nbsp; Nachdem sowohl die Zeitkoeffizienten&nbsp; d(ν)&nbsp; als auch alle Spektralkoeffizienten&nbsp; D(\mu)&nbsp; rein reell sind, besteht kein Unterschied zwischen der FFT und der IFFT.  
+
'''(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.
*Das bedeutet gleichzeitig:&nbsp; Die Eingangs– und Ausgangswerte können vertauscht werden.
+
*This means at the same time:&nbsp; The input and output values can be interchanged.
  
*Die Teilaufgabe&nbsp; '''(5)'''&nbsp; hat das folgende Ergebnis geliefert:
+
*Subtask&nbsp; '''(5)'''&nbsp; gave the following result:
 
   
 
   
:$$d({\rm gerades}\hspace{0.15cm}\nu) =  +1, \hspace{0.2cm}d({\rm
+
:$$d({\rm even}\hspace{0.15cm}\nu) =  +1, \hspace{0.2cm}d({\rm
ungerades}\hspace{0.15cm}\nu)=  -1$$
+
odd}\hspace{0.15cm}\nu)=  -1$$
 
:$$\Rightarrow
 
:$$\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&nbsp; '''(6)''':
+
*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}
 
:$$d(\nu = 4)= 1, \hspace{0.2cm}d(\nu \ne 4)= 0 \hspace{0.3cm}
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\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
*Insbesondere ergibt sich sich&nbsp; D(3) \; \underline{=  -1}&nbsp; und&nbsp; D(4) \; \underline{= +1}.
+
*In particular, this results in&nbsp; D(3) \; \underline{=  -1}&nbsp; und&nbsp; D(4) \; \underline{= +1}.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
 
__NOEDITSECTION__
 
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[[Category:Signal Representation: Exercises|^5.5 Fast Fourier Transform ^]]
 
[[Category:Signal Representation: Exercises|^5.5 Fast Fourier Transform ^]]

Revision as of 15:36, 23 March 2021

FFT algorithm for  N=8

The graph shows the signal flow diagram of the 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 = 1L =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 then available here.




Hint:



Questions

1

Calculate the DFT coefficient  D(3).

D(3) \ = \

2

Calculate the DFT coefficient  D(4).

D(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 = 4) \ = \

D(\mu \neq 4) \ = \

6

What would be the spectral coefficients for  d(ν = 4) = 1  and  d(ν \neq 4) = 0 ?
Enter the values  D(3)  and  D(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_1w_{12} = w_4w_{15} = w_7w_{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(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(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:   Es gilt  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  ww^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(4)} = {1}/{N}\cdot \left[Y(0) - Y(4) \right ] \hspace{0.15 cm}\underline{= 1} \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(3) \; \underline{= -1}  und  D(4) \; \underline{= +1}.