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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]]
+
[[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 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(\mu) =  \frac{1}{N}\cdot \sum_{\nu = 0 }^{N-1}
Line 11: Line 13:
 
  \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&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).
* Nach der dritten und letzten Stufe sind alle Werte noch durch&nbsp; N&nbsp; zu dividieren. Hier liegt dann das endgültige Ergebnis&nbsp; D(0), \hspace{0.03cm}\text{...} \hspace{0.1cm}  , D(7)&nbsp; vor.
+
* 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.
  
  
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''Hinweis:''  
+
''Hint:''  
*Die Aufgabe gehört zum  Kapitel&nbsp; [[Signal_Representation/Fast_Fourier_Transform_(FFT)|Fast-Fouriertransformation (FFT)]].
+
*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&nbsp; D(3).
+
{Calculate the DFT coefficient&nbsp; $D(\mu=3)$.
 
|type="{}"}
 
|type="{}"}
D(3) \ = \ { 0. }
+
$D(\mu=3) \ = \ $ { 0. }
  
{Berechnen Sie den DFT–Koeffizienten&nbsp; D(4).
+
{Calculate the DFT coefficient&nbsp; $D(\mu=4)$.
 
|type="{}"}
 
|type="{}"}
D(4) \ = \ { 1 3% }
+
$D(\mu=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.&nbsp; Which of the following statements are true?
 
|type="[]"}
 
|type="[]"}
- Alle&nbsp; X&ndash;Werte mit geradzahligen Indizes sind gleich&nbsp; 2.
+
- All&nbsp; X values with even indices are equal to&nbsp; 2.
+ Alle&nbsp; X&ndash;Werte mit ungeradzahligen Indizes sind gleich&nbsp; 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&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 =3) \ = \ { 0. }
 
D(\mu = 4) \ = \ { 1 3% }
 
D(\mu = 4) \ = \ { 1 3% }
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; $D(\mu =3)$&nbsp; and&nbsp; $D(\mu =4)$&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}-
Line 86: Line 89:
 
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; $\underline {D(\mu=3) = 0}$.
  
  
'''(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}+
 
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|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; It holds&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, 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&nbsp; '''(1)'''&nbsp; und&nbsp; '''(2)'''&nbsp; überein.  
+
This result agrees with the results from&nbsp; '''(1)'''&nbsp; und&nbsp; '''(2)'''.
  
  
  
'''(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}
Line 141: Line 146:
 
\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; $D(\mu=3) \; \underline{=  -1}&nbsp; und&nbsp; D(\mu=4) \; \underline{= +1}$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
 
__NOEDITSECTION__
 
__NOEDITSECTION__
 
[[Category:Signal Representation: Exercises|^5.5 Fast Fourier Transform ^]]
 
[[Category:Signal Representation: Exercises|^5.5 Fast Fourier Transform ^]]

Latest revision as of 18:08, 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 = 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 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_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(\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  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(\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}.