Difference between revisions of "Aufgaben:Exercise 4.6: Quantization Characteristics"

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{{quiz-Header|Buchseite=Modulationsverfahren/Pulscodemodulation
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{{quiz-Header|Buchseite=Modulation_Methods/Pulse_Code_Modulation
 
}}
 
}}
  
[[File:P_ID1623__Mod_Z_4_5.png|right|frame|Nichtlineare Quantisierungskennlinien]]
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[[File:EN_Mod_A_4_6_neu.png|right|frame|Non-linear quantization characteristics]]
Es wird die nichtlineare Quantisierung betrachtet und es gilt weiterhin das Systemmodell gemäß [[Aufgaben:4.5_Nichtlineare_Quantisierung| Aufgabe 4.5]].  
+
Non-linear quantization is considered.  The system model according to  [[Aufgaben:Exercise_4.5:_Non-Linear_Quantization| Exercise 4.5]] still applies.  
  
Die Grafik zeigt zwei Kompressorkennlinien  $q_{\rm K}(q_{\rm A})$:
+
The graph shows two compressor characteristics  $q_{\rm K}(q_{\rm A})$:
* Rot eingezeichnet ist die sogenannte '''A–Kennlinie''', die vom CCITT (''Comité Consultatif International Téléphonique et Télégraphique'') für das Standardsystem PCM 30/32 empfohlen wurde. Für  $0 ≤ q_{\rm A} ≤ 1$  gilt hier:
+
* Drawn in red is the so-called  "'''A-characteristic'''" recommended by the CCITT  ("Comité Consultatif International Téléphonique et Télégraphique")  for the standard system PCM 30/32.  For  $0 ≤ q_{\rm A} ≤ 1$  applies here:
:$$q_{\rm K}(q_{\rm A}) = \left\{ \begin{array}{l} \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A})} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \\ \frac{A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A}} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \end{array} \right.\quad \begin{array}{*{10}c} {\frac{1}{A} \le q_{\rm A} \le 1} \hspace{0.05cm}, \\ \\ {q_{\rm A} < \frac{1}{A}} \hspace{0.05cm}. \\ \end{array}$$
+
:$$q_{\rm K}(q_{\rm A}) = \left\{ \begin{array}{l} \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A})} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \\ \frac{A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A}} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \end{array} \right.\quad \begin{array}{*{10}c} {{1}/{A} \le q_{\rm A} \le 1} \hspace{0.05cm}, \\ \\ {q_{\rm A} < {1}/{A}} \hspace{0.05cm}. \\ \end{array}$$
* Der blau–gestrichelte Kurvenzug gilt für die so genannte '''13–Segment–Kennlinie'''. Diese ergibt sich aus der A–Kennlinie durch stückweise Linearisierung; sie wird in der [[Aufgaben:4.5_Nichtlineare_Quantisierung| Aufgabe 4.5]] ausführlich behandelt.
+
* The blue-dashed curve applies to the so-called&nbsp; "'''13-segment characteristic'''".&nbsp; This is obtained from the A-characteristic by piecewise linearization;&nbsp; it is treated in detail in the&nbsp; [[Aufgaben:Exercise_4.5:_Non-Linear_Quantization| Exercise 4.5]]&nbsp;.
  
  
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''Hinweise:''
+
 
*Die Aufgabe gehört zum  Kapitel&nbsp; [[Modulationsverfahren/Pulscodemodulation|Pulscodemodulation]].
+
Hints:  
*Bezug genommen wird insbesondere auf die Seite  [[Modulationsverfahren/Pulscodemodulation#Kompression_und_Expandierung|Kompression und Expandierung]].
+
*The Exercise belongs to the chapter&nbsp; [[Modulation_Methods/Pulse_Code_Modulation|"Pulse Code Modulation"]].
+
*Reference is made in particular to the page&nbsp; [[Modulation_Methods/Pulse_Code_Modulation#Compression_and_expansion|"Compression and Expansion"]].  
*Für die durchgehend rot gezeichnete A-Kennlinie ist der Quantisierungsparameter &nbsp;$A = 100$&nbsp; gewählt. Mit dem vom CCITT vorgeschlagenen Wert &nbsp;$A = 87.56$&nbsp; ergibt sich ein ähnlicher Verlauf.  
+
*For the A-characteristic drawn in solid red,&nbsp; the quantization parameter &nbsp;$A = 100$&nbsp; is chosen.&nbsp; With the value &nbsp;$A = 87.56$&nbsp; suggested by CCITT,&nbsp; a similar curve is obtained.  
*Für die beiden weiteren Kurven gilt &nbsp;$A = A_1$&nbsp; (strich&ndash;punktierte Kurve) bzw. &nbsp;$A = A_2$&nbsp; (punktierte Kurve), wobei für &nbsp;$A_1$&nbsp; bzw. &nbsp;$A_2$&nbsp; die beiden möglichen Zahlenwerte &nbsp;$50$&nbsp; und &nbsp;$200$&nbsp; vorgegeben sind. In der Teilaufgabe '''(3)''' sollen Sie entscheiden, welche Kurve zu welchem Zahlenwert gehört.
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*For the other two curves,
 +
:*&nbsp;$A = A_1$&nbsp; (dash&ndash;dotted curve) and
 +
:*&nbsp;$A = A_2$&nbsp; (dotted curve),&nbsp;
 +
 
 +
where for &nbsp;$A_1$&nbsp; and &nbsp;$A_2$&nbsp; the two possible numerical values &nbsp;$50$&nbsp; and &nbsp;$200$&nbsp; are given.&nbsp; In the subtask&nbsp; '''(3)'''&nbsp; you are to decide which curve belongs to which numerical value.
  
  
  
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche Argumente sprechen für die nichtlineare Quantisierung?
+
{What are the arguments for non-linear quantization?
 
|type="[]"}
 
|type="[]"}
- Das größere SNR – auch bei gleichwahrscheinlichen Amplituden.  
+
- The larger SNR &ndash; even with equally likely amplitudes.  
+ Bei Audio sind kleine Amplituden wahrscheinlicher als große.
+
+ For audio,&nbsp; small amplitudes are more likely than large ones.
+ Die Verfälschung kleiner Amplituden ist subjektiv störender.
+
+ The distortion of small amplitudes is subjectively more disturbing.
  
{Welche Unterschiede gibt es zwischen der A–Kennlinie und der 13–Segment–Kennlinie?
+
{What are the differences between the&nbsp; "A-characteristic" and the&nbsp; "13-segment characteristic"?
 
|type="[]"}
 
|type="[]"}
+ Die A–Kennlinie beschreibt einen kontinuierlichen Verlauf.
+
+ The A-characteristic curve describes a continuous course.
+ Die 13–Segment–Kurve nähert die A–Kennlinie stückweise linear an.
+
+ The 13-segment curve approximates the A-characteristic linearly piece by piece.
- Bei der Realisierung zeigt die A–Kennlinie wesentliche Vorteile.
+
- In the realization,&nbsp; the A-characteristic shows significant advantages.
  
{Lässt sich allein aus &nbsp;$q_{\rm A} = 1 &nbsp; &nbsp; &nbsp; &nbsp; q_{\rm K} = 1$&nbsp; der Parameter &nbsp;$A$&nbsp; ableiten?
+
{Can the parameter &nbsp;$A$&nbsp; be derived from &nbsp;$q_{\rm A} = 1$ &nbsp; &nbsp;  $q_{\rm K} = 1$&nbsp; alone?
|type="[]"}
+
|type="()"}
- Ja.  
+
- Yes.  
+ Nein.  
+
+ No.  
  
{Lässt sich &nbsp;$A$&nbsp; bestimmen, wenn man vorgibt, dass der Übergang zwischen den beiden Bereichen kontinuierlich sein soll?  
+
{Can the parameter &nbsp;$A$&nbsp; be determined if we specify that the transition between the two domains should be continuous?  
|type="[]"}
+
|type="()"}
- Ja.  
+
- Yes.  
+ Nein.  
+
+ No.  
  
{Bestimmen Sie &nbsp;$A$&nbsp; aus der Bedingung &nbsp;$q_{\rm K}(q_{\rm K} = 1/2) = 0.8756$.
+
{Determine the parameter &nbsp;$A$&nbsp; from the condition &nbsp;$q_{\rm K}(q_{\rm A} = 1/2) = 0.8756$.
 
|type="{}"}
 
|type="{}"}
 
$A \ = \ $ { 94 3% }  
 
$A \ = \ $ { 94 3% }  
  
{Welche Parameterwerte wurden für die weiteren Kurven verwendet?
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{What parameter values were used for the other curves?
|type="[]"}
+
|type="()"}
- Es gilt &nbsp;$A_1 = 50$&nbsp; und &nbsp;$A_2 = 200$.
+
- It holds &nbsp;$A_1 = 50$&nbsp; and &nbsp;$A_2 = 200$.
+ Es gilt &nbsp;$A_1 = 200$&nbsp; und &nbsp;$A_2 = 50$.
+
+ It holds &nbsp;$A_1 = 200$&nbsp; and &nbsp;$A_2 = 50$.
 
 
  
  
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</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
  
'''(1)'''&nbsp; Richtig sind die <u>Aussagen 2 und 3</u>:  
+
'''(1)'''&nbsp; Correct are the&nbsp; <u>statements 2 and 3</u>:  
*Eine Signalverfälschung von leisen Tönen oder in Sprachpausen wird subjektiv als störender empfunden als zum Beispiel ein zusätzliches Geräusch bei Heavy Metal.  
+
*Signal distortion of soft sounds or in speech pauses is subjectively perceived as more disturbing than e.g. additional noise in heavy metal.  
*Bezüglich des Quantisierungsrauschens bzw. des SNR gibt es durch eine nichtlineare Quantisierung allerdings keine Verbesserung, wenn von einer Gleichverteilung der Amplitudenwerte ausgegangen wird.  
+
*In terms of quantization noise or SNR,&nbsp; however,&nbsp; there is no improvement due to non-linear quantization if an uniformly distribution of the amplitude values is assumed.  
*Berücksichtigt man aber, dass bei Sprach– und Musiksignalen kleinere Amplituden sehr viel häufiger auftreten als große &nbsp; &Rarr; &nbsp; ''Laplaceverteilung'', so ergibt sich durch die nichtlineare Quantisierung auch ein besseres SNR.
+
*However,&nbsp; if one considers that in speech and music signals smaller amplitudes occur much more frequently than large &nbsp; &rArr; &nbsp; "Laplace distribution",&nbsp; non-linear quantization also results in a better SNR.
 +
 
 +
 
 +
 
 +
'''(2)'''&nbsp; Correct are the&nbsp;<u>statements 1 and 2</u>:
 +
*Due to the linearization in the individual segments,&nbsp; the interval width of the various quantization levels is constant in these for the&nbsp; "13-segment characteristic",&nbsp; which has a favorable effect in realization.
 +
*In contrast,&nbsp; with the non-linear quantization according to the&nbsp; "A-characteristic",&nbsp; there are no quantization intervals of equal width.&nbsp; <br>This means: &nbsp; The statement 3 is false.
  
  
'''(2)'''&nbsp; Richtig sind die <u>Aussagen 1 und 2</u>:
 
*Durch die Linearisierung in den einzelnen Segmenten ist in diesen bei der 13–Segment–Kennlinie die Intervallbreite der verschiedenen Quantisierungsstufen konstant, was sich bei der Realisierung günstig auswirkt.
 
*Dagegen gibt es bei der nichtlinearen Quantisierung gemäß der A–Kennlinie keine Quantisierungsintervalle gleicher Breite. Das bedeutet: Die Aussage 3 ist falsch.
 
  
 +
'''(3)'''&nbsp; Correct is&nbsp; "<u>NO</u>":
 +
*For&nbsp; $q_{\rm A} = 1$&nbsp; one obtains independently of&nbsp; $A$&nbsp; the value&nbsp; $q_{\rm K} = 1$.
 +
*So with this specification alone&nbsp; $A$&nbsp; cannot be determined.
 +
  
'''(3)'''&nbsp; Richtig ist <u>NEIN</u>:
 
*Für $q_{\rm A} = 1$ erhält man unabhängig von $A$ den Wert $q_{\rm A} = 1$.
 
*Allein mit dieser Vorgabe kann $A$ also nicht ermittelt werden.
 
  
 +
'''(4)'''&nbsp; Correct is again&nbsp; "<u>NO</u>":
 +
*For&nbsp; $q_{\rm A} = 1/A$&nbsp; both range equations yield the same value&nbsp; $q_{\rm K}= 1/[1 + \ln(A)]$.
 +
*Also with this&nbsp; $A$&nbsp; cannot be determined.
  
'''(4)'''&nbsp; Richtig is twiederum  <u>NEIN</u>:
 
*Für $q_{\rm A} = 1/A$ liefern beide Bereichsgleichungen den gleichen Wert $q_{\rm K}= 1/[1 + \ln(A)]$.
 
*Auch damit kann $A$ nicht bestimmt werden.
 
  
  
'''(5)'''&nbsp; Mit dieser Forderung ist $A$ nun berechenbar:
+
'''(5)'''&nbsp; With this requirement&nbsp; $A$&nbsp; is now computable:
 
:$$0.875 = \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A/2)} {1
 
:$$0.875 = \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A/2)} {1
 
\hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} =
 
\hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} =
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94} \hspace{0.05cm}.$$
 
94} \hspace{0.05cm}.$$
  
'''(6)'''&nbsp; Richtig ist die <u>Aussage 2</u>:
+
 
*Die Kurve für $A_1 = 200$ liegt oberhalb der Kurve mit $A = 100$, die Kurve mit $A_2 = 50$ unterhalb.  
+
 
*Dies zeigt die folgende Rechnung für $q_{\rm A} = 0.5$:
+
'''(6)'''&nbsp; Correct is&nbsp; <u>statement 2</u>:
 +
*The curve for &nbsp;$A_1 = 200$&nbsp; lies above the curve with &nbsp;$A = 100$,&nbsp; the curve with &nbsp;$A_2 = 50$&nbsp; below.  
 +
*This is shown by the following calculation for &nbsp;$q_{\rm A} = 0.5$:
 
:$$A= 100\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1 + \ln(100) - \ln(2)}{1 + \ln(100)}=
 
:$$A= 100\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1 + \ln(100) - \ln(2)}{1 + \ln(100)}=
 
\frac{1+4.605- 0.693} {1 +4.605}\approx
 
\frac{1+4.605- 0.693} {1 +4.605}\approx
0.876 \hspace{0.05cm},$$
+
0.876 \hspace{0.05cm},$$
 
:$$A= 200\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1+5.298- 0.693} {1 +5.298}\approx
 
:$$A= 200\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1+5.298- 0.693} {1 +5.298}\approx
0.890 \hspace{0.05cm},$$
+
0.890 \hspace{0.05cm},$$
 
:$$A= 50\text{:}\hspace{0.4cm} q_{\rm K}= \frac{1+3.912- 0.693} {1 +3.912}\approx
 
:$$A= 50\text{:}\hspace{0.4cm} q_{\rm K}= \frac{1+3.912- 0.693} {1 +3.912}\approx
0.859 \hspace{0.05cm}.$$
+
0.859 \hspace{0.05cm}.$$
  
  
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[[Category:Aufgaben zu Modulationsverfahren|^4.1 Pulscodemodulation^]]
+
[[Category:Modulation Methods: Exercises|^4.1 Pulse Code Modulation^]]

Latest revision as of 15:01, 11 April 2022

Non-linear quantization characteristics

Non-linear quantization is considered.  The system model according to  Exercise 4.5 still applies.

The graph shows two compressor characteristics  $q_{\rm K}(q_{\rm A})$:

  • Drawn in red is the so-called  "A-characteristic" recommended by the CCITT  ("Comité Consultatif International Téléphonique et Télégraphique")  for the standard system PCM 30/32.  For  $0 ≤ q_{\rm A} ≤ 1$  applies here:
$$q_{\rm K}(q_{\rm A}) = \left\{ \begin{array}{l} \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A})} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \\ \frac{A \hspace{0.05cm}\cdot \hspace{0.05cm}q_{\rm A}} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} \\ \end{array} \right.\quad \begin{array}{*{10}c} {{1}/{A} \le q_{\rm A} \le 1} \hspace{0.05cm}, \\ \\ {q_{\rm A} < {1}/{A}} \hspace{0.05cm}. \\ \end{array}$$
  • The blue-dashed curve applies to the so-called  "13-segment characteristic".  This is obtained from the A-characteristic by piecewise linearization;  it is treated in detail in the  Exercise 4.5 .




Hints:

  • The Exercise belongs to the chapter  "Pulse Code Modulation".
  • Reference is made in particular to the page  "Compression and Expansion".
  • For the A-characteristic drawn in solid red,  the quantization parameter  $A = 100$  is chosen.  With the value  $A = 87.56$  suggested by CCITT,  a similar curve is obtained.
  • For the other two curves,
  •  $A = A_1$  (dash–dotted curve) and
  •  $A = A_2$  (dotted curve), 

where for  $A_1$  and  $A_2$  the two possible numerical values  $50$  and  $200$  are given.  In the subtask  (3)  you are to decide which curve belongs to which numerical value.



Questions

1

What are the arguments for non-linear quantization?

The larger SNR – even with equally likely amplitudes.
For audio,  small amplitudes are more likely than large ones.
The distortion of small amplitudes is subjectively more disturbing.

2

What are the differences between the  "A-characteristic" and the  "13-segment characteristic"?

The A-characteristic curve describes a continuous course.
The 13-segment curve approximates the A-characteristic linearly piece by piece.
In the realization,  the A-characteristic shows significant advantages.

3

Can the parameter  $A$  be derived from  $q_{\rm A} = 1$   ⇒   $q_{\rm K} = 1$  alone?

Yes.
No.

4

Can the parameter  $A$  be determined if we specify that the transition between the two domains should be continuous?

Yes.
No.

5

Determine the parameter  $A$  from the condition  $q_{\rm K}(q_{\rm A} = 1/2) = 0.8756$.

$A \ = \ $

6

What parameter values were used for the other curves?

It holds  $A_1 = 50$  and  $A_2 = 200$.
It holds  $A_1 = 200$  and  $A_2 = 50$.


Solution

(1)  Correct are the  statements 2 and 3:

  • Signal distortion of soft sounds or in speech pauses is subjectively perceived as more disturbing than e.g. additional noise in heavy metal.
  • In terms of quantization noise or SNR,  however,  there is no improvement due to non-linear quantization if an uniformly distribution of the amplitude values is assumed.
  • However,  if one considers that in speech and music signals smaller amplitudes occur much more frequently than large   ⇒   "Laplace distribution",  non-linear quantization also results in a better SNR.


(2)  Correct are the statements 1 and 2:

  • Due to the linearization in the individual segments,  the interval width of the various quantization levels is constant in these for the  "13-segment characteristic",  which has a favorable effect in realization.
  • In contrast,  with the non-linear quantization according to the  "A-characteristic",  there are no quantization intervals of equal width. 
    This means:   The statement 3 is false.


(3)  Correct is  "NO":

  • For  $q_{\rm A} = 1$  one obtains independently of  $A$  the value  $q_{\rm K} = 1$.
  • So with this specification alone  $A$  cannot be determined.


(4)  Correct is again  "NO":

  • For  $q_{\rm A} = 1/A$  both range equations yield the same value  $q_{\rm K}= 1/[1 + \ln(A)]$.
  • Also with this  $A$  cannot be determined.


(5)  With this requirement  $A$  is now computable:

$$0.875 = \frac{1 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A/2)} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )} = \frac{1\hspace{0.05cm}-\hspace{0.05cm} {\rm ln}(2) \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A)} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )}\approx \frac{1-0.693 \hspace{0.05cm}+\hspace{0.05cm} {\rm ln}(A)} {1 \hspace{0.05cm}+ \hspace{0.05cm}{\rm ln}(A )}\hspace{0.3cm} \Rightarrow \hspace{0.3cm}{\rm ln}(A) = \frac{0.875 - 0.307 } {1 -0.875 }= 4.544 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} A \hspace{0.15cm}\underline {\approx 94} \hspace{0.05cm}.$$


(6)  Correct is  statement 2:

  • The curve for  $A_1 = 200$  lies above the curve with  $A = 100$,  the curve with  $A_2 = 50$  below.
  • This is shown by the following calculation for  $q_{\rm A} = 0.5$:
$$A= 100\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1 + \ln(100) - \ln(2)}{1 + \ln(100)}= \frac{1+4.605- 0.693} {1 +4.605}\approx 0.876 \hspace{0.05cm},$$
$$A= 200\text{:}\hspace{0.2cm} q_{\rm K}= \frac{1+5.298- 0.693} {1 +5.298}\approx 0.890 \hspace{0.05cm},$$
$$A= 50\text{:}\hspace{0.4cm} q_{\rm K}= \frac{1+3.912- 0.693} {1 +3.912}\approx 0.859 \hspace{0.05cm}.$$