Aufgaben:Exercise 3.2Z: Laplace and Fourier: Difference between revisions

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[[File:P_ID1764__LZI_Z_3_2.png|right|frame|Four causal time signals]]
[[File:P_ID1764__LZI_Z_3_2.png|right|frame|Four causal time signals]]
The Fourier transformation can be applied to any deterministic signal  $x(t)$ . Then, the following holds for the spectral function:
The Fourier transformation can be applied to any deterministic signal  $x(t)$.  Then, the following holds for the spectral function:
:$$X(f) =    \int_{-\infty}^{
:$$X(f) =    \int_{-\infty}^{
+\infty}
+\infty}
Line 10: Line 10:
  d}t\hspace{0.05cm}\hspace{0.05cm} .$$
  d}t\hspace{0.05cm}\hspace{0.05cm} .$$


For power-limited signals – characteristics:   infinite energy – $X(f)$  also includes distributions (Dirac functions).
For power-limited signals  – characteristics:   infinite energy –  $X(f)$  also includes distributions  (Dirac delta  functions).


For all causal signals (and only for these), the Laplace transformation is also applicable beside the Fourier transformation:
For all causal signals  (and only for these),  the Laplace transformation is also applicable beside the Fourier transformation:
:$$X_{\rm L}(p) =    \int_{0}^{
:$$X_{\rm L}(p) =    \int_{0}^{
\infty}
\infty}
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In the diagram you can see several causal time functions that will be covered in this exercise:
In the diagram you can see several causal time functions that will be covered in this exercise:


* the Dirac function  $a(t)$,
* the Dirac delta function  $a(t)$,


* the step function  $b(t)$,
* the unit step function  $b(t)$,


* the rectangular function  $c(t)$,
* the rectangular function  $c(t)$,
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The  [[Signal_Representation/Fourier_Transform_Theorems|Fourier transform theorems]]  usually (though not always) also apply to the Laplace transformation where  $p ={\rm j} \cdot 2 \pi f$  is to be set:
The  [[Signal_Representation/Fourier_Transform_Theorems|Fourier transform theorems]]  usually  (though not always)  also apply to the Laplace transformation where  $p ={\rm j} \cdot 2 \pi f$  is to be set:


* For example, the  [[Signal_Representation/Fourier_Transform_Theorems#Shifting_Theorem|shifting theorem]]  in Laplace or Fourier representation is:
* For example,  the  [[Signal_Representation/Fourier_Transform_Theorems#Shifting_Theorem|shifting theorem]]  in Laplace or Fourier representation is:
:$$x(t- \tau) \quad
:$$x(t- \tau) \quad
\circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm
\circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm
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X(f)\cdot {\rm e}^{-{\rm j}\hspace{0.05cm} \cdot \hspace{0.05cm}2\pi f \hspace{0.05cm} \cdot \hspace{0.05cm}\tau}\hspace{0.05cm} .$$
X(f)\cdot {\rm e}^{-{\rm j}\hspace{0.05cm} \cdot \hspace{0.05cm}2\pi f \hspace{0.05cm} \cdot \hspace{0.05cm}\tau}\hspace{0.05cm} .$$


* In contrast, there are differences in the  [[Signal_Representation/Fourier_Transform_Theorems#Integration_Theorem|integration theorem]] :
* In contrast,  there are differences in the  [[Signal_Representation/Fourier_Transform_Theorems#Integration_Theorem|integration theorem]] :
:$$\int {x(\tau)} \hspace{0.1cm}{\rm
:$$\int {x(\tau)} \hspace{0.1cm}{\rm
  d}\tau \quad
  d}\tau \quad
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Please note:  
 
 
''Please note:''
*The exercise belongs to the chapter  [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function|Laplace Transform and p-Transfer Function]].
*The exercise belongs to the chapter  [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function|Laplace Transform and p-Transfer Function]].
*The educational video   [[Gesetzmäßigkeiten_der_Fouriertransformation_(Lernvideo)|Fourier transform theorems]]  might be helpful.
*The educational video   [[Gesetzmäßigkeiten_der_Fouriertransformation_(Lernvideo)|Fourier transform theorems]]  might be helpful.

Revision as of 14:09, 13 October 2021

Four causal time signals

The Fourier transformation can be applied to any deterministic signal  $x(t)$.  Then, the following holds for the spectral function:

$$X(f) = \int_{-\infty}^{

+\infty}

{ x(t) \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm e}^{-{\rm j}\hspace{0.05cm}\cdot \hspace{0.05cm}2\pi f t}}\hspace{0.1cm}{\rm
d}t\hspace{0.05cm}\hspace{0.05cm} .$$

For power-limited signals  – characteristics:   infinite energy –  $X(f)$  also includes distributions  (Dirac delta functions).

For all causal signals  (and only for these),  the Laplace transformation is also applicable beside the Fourier transformation:

$$X_{\rm L}(p) = \int_{0}^{

\infty}

{ x(t) \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm e}^{-p t}}\hspace{0.1cm}{\rm
d}t\hspace{0.05cm}\hspace{0.05cm} .$$

In the diagram you can see several causal time functions that will be covered in this exercise:

  • the Dirac delta function  $a(t)$,
  • the unit step function  $b(t)$,
  • the rectangular function  $c(t)$,
  • the ramp function  $d(t)$.


The  Fourier transform theorems  usually  (though not always)  also apply to the Laplace transformation where  $p ={\rm j} \cdot 2 \pi f$  is to be set:

  • For example,  the  shifting theorem  in Laplace or Fourier representation is:
$$x(t- \tau) \quad

\circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm L}\!\!\!-\!\!\hspace{-0.05cm}\bullet\quad X_{\rm L}(p)\cdot {\rm e}^{-p \hspace{0.05cm} \cdot \hspace{0.05cm}\tau}\hspace{0.05cm} ,$$

$$x(t- \tau) \quad

\circ\!\!-\!\!\!-^{\hspace{-0.05cm}}\!\!\!-\!\!\hspace{-0.05cm}\bullet\quad X(f)\cdot {\rm e}^{-{\rm j}\hspace{0.05cm} \cdot \hspace{0.05cm}2\pi f \hspace{0.05cm} \cdot \hspace{0.05cm}\tau}\hspace{0.05cm} .$$

$$\int {x(\tau)} \hspace{0.1cm}{\rm
d}\tau \quad

\circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm L}\!\!\!-\!\!\hspace{-0.05cm}\bullet\quad X_{\rm L}(p)\cdot \frac{1}{p}\hspace{0.05cm} ,$$

$$\int {x(\tau)} \hspace{0.1cm}{\rm
d}\tau \quad

\circ\!\!-\!\!\!-^{\hspace{-0.05cm}}\!\!\!-\!\!\hspace{-0.05cm}\bullet\quad X(f)\cdot \left [ {1}/{2} \cdot{\rm \delta } (f) + \frac{1}{{\rm j} \cdot 2\pi f} \right ] \hspace{0.05cm} .$$




Please note:


Questions

1 What are the spectral transformations of the signal  $a(t) = \delta(t)$?

$A_{\rm L}(p) = 1$.
$A(f) = \delta(f)$.
$A(f) = 1$.

2 What are the spectral transformations of the step function  $b(t) = \gamma(t)$?

$B_{\rm L}(p) = 1/p$.
$B(f) = 1/({\rm j} \cdot 2 \pi f)$
$B(f) = 1/2 \cdot \delta(f) - {\rm j}/(2 \pi f)$.

3 What are the spectral transformations of the rectangular function  $c(t)$?

$C_{\rm L}(p) = {\rm si}(pT)$.
$C_{\rm L}(p) = \big [1-{\rm e}^{-p\hspace{0.05cm} \cdot \hspace{0.05cm}T} \big ]/p$.
$C(f) = C_{\rm L}(p)$  mit  $p = 2 \pi f$.

4 What are the spectral transformations of the ramp function  $d(t)$?

$D_{\rm L}(p) = \big[1-{\rm e}^{-p\hspace{0.05cm} \cdot \hspace{0.05cm}T}\big]/(p^2T)$.
$D_{\rm L}(p) = 1-{\rm e}^{-p\hspace{0.05cm} \cdot \hspace{0.05cm}T}$.
$D(f) = D_{\rm L}(p)$  mit  $p = 2 \pi f$.


Solution

(1)  Suggested solutions 1 and 3 are correct:

  • Considering that the Dirac function is non-zero only at  $t= 0$  and that the integral over the Dirac yields the value  $1$  as long as the integration interval includes the time  $t= 0$,  the following is obtained:
$$A(f) = 1, \hspace{0.2cm}A_{\rm
L}(p) = 1  \hspace{0.05cm} .$$


(2)  Suggested solutions 1 and 3 are correct again:

  • The step function  $b(t) = \gamma(t)$  is the integral over the Dirac function  $a(t) = \delta(t)$   ⇒   the  integration theorem  can be applied:
$$b(t) = \int_{-\infty}^t {a(\tau)} \hspace{0.1cm}{\rm
d}\tau  \hspace{0.3cm}\Rightarrow \hspace{0.3cm} B_{\rm L}(p) =A_{\rm L}(p)\cdot

{1}/{p} = {1}/{p}\hspace{0.05cm} ,$$

$$B(f) = A(f)\cdot \left [ {1}/{2} \cdot{\rm \delta } (f) +

\frac{1}{{\rm j} \cdot 2\pi f} \right ] = {1}/{2} \cdot{\rm \delta } (f) + \frac{1}{{\rm j} \cdot 2\pi f}\hspace{0.05cm} .$$


(3)  Suggested solutions 2 and 3 are correct:

  • Since the (causal) rectangular function can be represented as the difference of two step functions, the  shifting theorem yields:
$$c(t)= b(t) - b(t-T) \hspace{0.3cm}

\Rightarrow \hspace{0.3cm} C_{\rm L}(p) =B_{\rm L}(p)- B_{\rm L}(p)

\cdot {\rm e}^{-p \hspace{0.05cm} \cdot \hspace{0.05cm}T} = {1}/{p} \cdot \big [ 1- {\rm e}^{-p \hspace{0.05cm} \cdot \hspace{0.05cm}T} \big ]
\hspace{0.05cm} .$$
  • The following holds for the  Fourier spectrum since the rectangular function has finite energy:
$$C(f) = C_{\rm L}(p)\Bigg |_{\hspace{0.1cm} p\hspace{0.05cm}=\hspace{0.05cm}{\rm j \hspace{0.05cm}2\pi \it
f}} =   \frac{1}{{\rm j} \cdot 2\pi f} \cdot \big [ 1- {\rm e}^{-{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm} 2\pi f T} \big ]
\hspace{0.05cm}.$$
  • The following can also be written for this using some trigonometric transformations:
$$C(f) = T \cdot {\rm si} (2 \pi f{T})+ {\rm j} \cdot \frac{{\rm cos} (2 \pi f{T})-1}{2\pi f}
\hspace{0.05cm}.$$


(4)  Suggested solution 1 is correct because the following holds:

$$d(t) = \frac{1}{T} \cdot \int\limits_{-\infty}^t {c(\tau)} \hspace{0.1cm}{\rm
d}\tau  \hspace{0.3cm}\Rightarrow \hspace{0.3cm} D_{\rm L}(p) =C_{\rm L}(p)\cdot

\frac{1}{p \cdot T} = \frac{1- {\rm e}^{-p \hspace{0.05cm}\cdot \hspace{0.05cm}T}}{p^2 \cdot T}\hspace{0.05cm} .$$

  • Since  $d(t)$  extends to infinity, the simple relation between  $D_{\rm L}(p)$  and  $D(f)$  according to proposed solution 3 is not valid.
  • $D(f)$  rather also includes a Dirac function at frequency  $f = 0$.