We consider here a binay signal $b(t)$ and a quaternaryärsignal $q(t)$, where:
We consider here a binay signal $b(t)$ and a quaternary signal $q(t)$.
*The two signals are rectangular in shape, and the duration of each rectangle is $T$ (symbol duration).
*The two signals are rectangular in shape. The duration of each rectangle is $T$ (symbol duration).
*The symbols represented by the pulse heights of the individual rectangular pulses $($with step number $M = 2$ or $M = 4)$ are statistically independent.
*The symbols represented by the pulse heights of the individual rectangular pulses $($with step number $M = 2$ or $M = 4)$ are statistically independent.
*Because of the bipolar signal constellation, both signals are have no DC values if the symbol probabilities are chosen appropriately (symmetrically).
*Because of the bipolar signal constellation, both signals have no DC component if the symbol probabilities are chosen appropriately (symmetrically).
*Because of the latter property, it follows for the probabilities of the binary symbols:
*Because of the latter property, it follows for the probabilities of the binary symbols:
{What is the magnitude of the ACF–value when $\tau = T$ ? Justify why the ACF–values for $\tau| > T$ are the same size. Sketch the ACF–progression.
{What is the magnitude of the ACF value when $\tau = T$ ? Justify why the ACF values for $|\tau| > T$ are of the same size. Sketch the ACF diagram.
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$\varphi_q(\tau = T) \ = \ $ { 0. } $\ \rm V^2$
$\varphi_q(\tau = T) \ = \ $ { 0. } $\ \rm V^2$
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{With which amplitude values $(\pm b_0)$ does the binary signal $b(t)$ have exactly the same ASF?
{With which amplitude values $(\pm b_0)$ does the binary signal $b(t)$ have exactly the same ACF?
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$b_0\ = \ $ { 1.915 3% } $\ \rm V$
$b_0\ = \ $ { 1.915 3% } $\ \rm V$
{Which of the following descriptive quantities of a stochastic process can be determined from the AKF?
{Which of the following descriptive quantities of a stochastic process can be determined from the ACF?
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+ period duration.
+ Period duration.
- Probability density function.
- Probability density function.
+ Linear mean value.
+ Linear mean value.
+ Variance.
+ Variance.
- 3rd order moment.
- 3rd order moment.
-phase relations.
- Phase relations.
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===Solution===
===Solution===
{{ML-Kopf}}
{{ML-Kopf}}
'''(1)''' The ACF value at the point $\tau = 0$ corresponds to the mean signal power, i.e. the root mean square value of $q(t)$. For this holds:
'''(1)''' The ACF value at the point $\tau = 0$ corresponds to the mean signal power, i.e. the variance of $q(t)$. For this holds:
*Thus, the ACF we are looking for has the shape sketched on the right.
*Thus, the ACF we are looking for has the shape sketched on the right.
*In the range $-T \le \tau \le +T$ the ACF is sectionwise linear, i.e. triangular, due to the rectangular pulse shape.
*In the range $-T \le \tau \le +T$ the ACF is sectionwise linear, i.e. triangular, due to the rectangular pulse shape.
<br clear=all>
<br clear=all>
'''(3)''' The ACF $\varphi_b(\tau)$ of the binary signal is also identically zero due to the statistically independent symbols in the range $| \tau| > T$ and for $-T \le \tau \le +T$ also results in a triangular shape.
'''(3)''' The ACF $\varphi_b(\tau)$ of the binary signal is also identically zero due to the statistically independent symbols in the range $| \tau| > T$.
*For the quadratic mean, one obtains:
*For $-T \le \tau \le +T$ itnalso results in a triangular shape.
*For the second moment, one obtains:
:$$\varphi_b (\tau = 0) = b_{\rm 0}^{\rm 2}.$$
:$$\varphi_b (\tau = 0) = b_{\rm 0}^{\rm 2}.$$
*With $b_0\hspace{0.15cm}\underline{= 1.915\, \rm V}$ the two autocorrelation functions $\varphi_q(\tau)$ and $\varphi_b(\tau)$ are identical.
*With $b_0\hspace{0.15cm}\underline{= 1.915\, \rm V}$ the two auto-correlation functions $\varphi_q(\tau)$ and $\varphi_b(\tau)$ are identical.
'''(4)''' Correct are <u>the proposed solutions 1, 3, and 4</u>.
'''(4)''' Correct are <u>the proposed solutions 1, 3, and 4</u>.
From the autocorrelation function we can actually determine:
From the autocorrelation function we can actually determine:
*the period $T_0$: this is the same for the pattern signals and the ACF;
*The period $T_0$: this is the same for the pattern signals and the ACF;
* the linear mean: root of the final value of the ACF for $\tau \to \infty$ and
* the linear mean: root of the final value of the ACF for $\tau \to \infty$;
* the variance: difference of the ACF values of $\tau = 0$ and $\tau \to \infty$.
* the variance: difference of the ACF values of $\tau = 0$ and $\tau \to \infty$.
Cannot be determined:
Cannot be determined:
* the probability density function: despite $\varphi_q(\tau) =\varphi_b(\tau)$ is $f_q(q) \ne f_b(b)$;
* The probability density function $\rm (PDF)$: <br> despite $\varphi_q(\tau) =\varphi_b(\tau)$ ⇒ $f_q(q) \ne f_b(b)$;
* the moments of higher order: for their calculation one needs the PDF;
* the moments of higher order: <br> for their calculation one needs the PDF;
* All phase relations and symmetry properties are not recognizable from the ACF.
* all phase relations and symmetry properties are not recognizable from the ACF.
{{ML-Fuß}}
{{ML-Fuß}}
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[[Category:Theory of Stochastic Signals: Exercises|^4.4 Auto-Correlation Function^]]
[[Category:Theory of Stochastic Signals: Exercises|^4.4 Auto-Correlation Function^]]
We consider here a binay signal $b(t)$ and a quaternary signal $q(t)$.
The two signals are rectangular in shape. The duration of each rectangle is $T$ (symbol duration).
The symbols represented by the pulse heights of the individual rectangular pulses $($with step number $M = 2$ or $M = 4)$ are statistically independent.
Because of the bipolar signal constellation, both signals have no DC component if the symbol probabilities are chosen appropriately (symmetrically).
Because of the latter property, it follows for the probabilities of the binary symbols:
(1) The ACF value at the point $\tau = 0$ corresponds to the mean signal power, i.e. the variance of $q(t)$. For this holds:
Triangular auto-correlation function