Difference between revisions of "Aufgaben:Exercise 5.4: Comparison of Rectangular and Hanning Window"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Signal_Representation/Spectrum_Analysis |
}} | }} | ||
− | [[File:P_ID1166__Sig_A_5_4_neu.png|250px|right| | + | [[File:P_ID1166__Sig_A_5_4_neu.png|250px|right|frame|Examples for spectral analysis]] |
− | + | Let the time course of a periodic signal be given in principle: | |
− | $$ | + | :$$x(t) = A_1 \cdot \cos (2 \pi \cdot f_1 \cdot t) + A_2 \cdot \cos (2 \pi \cdot f_2 \cdot t) \hspace{0.05cm}.$$ |
− | + | ||
+ | Unknown and thus to be estimated are its parameters $A_1$, $f_1$, $A_2$ and $f_2$. | ||
+ | |||
+ | After weighting the signal with the window function $w(t)$ , the product $y(t) = x(t) \cdot w(t)$ is subjected to a [[Signal_Representation/Discrete_Fourier_Transform_(DFT)|Discrete Fourier Transform]] (DFT) with the parameters $N = 512$ and $T_{\rm P}$. The time $T_{\rm P}$ of the signal section to be analyzed can be set by the user as desired. | ||
− | + | Two functions are available for windowing, each of which is zero for $|t| > T_{\rm P}/2$: | |
− | + | *The '''rectangular window''': | |
− | |||
− | $${w} (\nu) = \left\{ \begin{array}{c} 1 \\ | + | :$${w} (\nu) = \left\{ \begin{array}{c} 1 \\ |
0 \\ \end{array} \right.\quad | 0 \\ \end{array} \right.\quad | ||
− | \begin{array}{*{10}c} {\rm{ | + | \begin{array}{*{10}c} {\rm{for}} |
\\ \\ \end{array}\begin{array}{*{20}c} | \\ \\ \end{array}\begin{array}{*{20}c} | ||
-N/2 \le \nu < N/2 \hspace{0.05cm}, \\ | -N/2 \le \nu < N/2 \hspace{0.05cm}, \\ | ||
− | {\rm | + | {\rm else} \hspace{0.05cm}, \\ |
\end{array}$$ | \end{array}$$ | ||
− | $$W(f) ={1}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot | + | :$$W(f) ={1}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot |
{f}/{f_{\rm A}})\hspace{0.05cm},$$ | {f}/{f_{\rm A}})\hspace{0.05cm},$$ | ||
− | + | *the '''Hanning window''': | |
− | $${w} (\nu) = \left\{ \begin{array}{c} 0.5 + 0.5 \cdot \cos (2 \pi \cdot | + | :$${w} (\nu) = \left\{ \begin{array}{c} 0.5 + 0.5 \cdot \cos (2 \pi \cdot {\nu}/{N}) \\ |
0 \\ \end{array} \right.\quad | 0 \\ \end{array} \right.\quad | ||
− | \begin{array}{*{10}c} {\rm{ | + | \begin{array}{*{10}c} {\rm{for}} |
\\ \\ \end{array}\begin{array}{*{20}c} | \\ \\ \end{array}\begin{array}{*{20}c} | ||
-N/2 \le \nu < N/2 \hspace{0.05cm}, \\ | -N/2 \le \nu < N/2 \hspace{0.05cm}, \\ | ||
− | {\rm | + | {\rm else} \hspace{0.05cm}, \\ |
\end{array}$$ | \end{array}$$ | ||
− | $$W(f) ={0.5}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot | + | :$$W(f) ={0.5}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot |
\frac{f}{f_{\rm A}})+ {0.25}/{f_{\rm A}}\cdot {\rm si}(\pi | \frac{f}{f_{\rm A}})+ {0.25}/{f_{\rm A}}\cdot {\rm si}(\pi | ||
\cdot \frac{f-f_{\rm A}}{f_{\rm A}})+ {0.5}/{f_{\rm A}}\cdot | \cdot \frac{f-f_{\rm A}}{f_{\rm A}})+ {0.5}/{f_{\rm A}}\cdot | ||
{\rm si}(\pi \cdot \frac{f+f_{\rm A}}{f_{\rm A}})\hspace{0.05cm}.$$ | {\rm si}(\pi \cdot \frac{f+f_{\rm A}}{f_{\rm A}})\hspace{0.05cm}.$$ | ||
− | + | Here, $W(f)$ is the Fourier transform of the continuous-time window function $w(t)$, while $w(ν)$ indicates the discrete-time weighting function. | |
− | + | ||
+ | In the task, reference is made to various spectral functions $Y(f)$ for example to | ||
− | $$Y_{\rm A}(f) = 1\, {\rm V}\cdot {\rm \delta} (f \pm 1\,\,{\rm kHz})+ | + | :$$Y_{\rm A}(f) = 1\, {\rm V}\cdot {\rm \delta} (f \pm 1\,\,{\rm kHz})+ |
0.5\,\, {\rm V}\cdot {\rm \delta} (f \pm 1.125\,\,{\rm kHz}) | 0.5\,\, {\rm V}\cdot {\rm \delta} (f \pm 1.125\,\,{\rm kHz}) | ||
\hspace{0.05cm}.$$ | \hspace{0.05cm}.$$ | ||
− | In | + | In the graph, two further spectral functions $Y_{\rm B}(f)$ and $Y_{\rm C}(f)$ are shown, which result when a $1 \ \text{kHz}$ signal is analyzed by DFT and the DFT parameter $T_{\rm P} = 8.5 \ \text{ms}$ is chosen unfavourably. |
− | + | ||
− | + | *For one of the images the rectangular window is used, for the other the Hanning window. | |
+ | *It is not indicated which graph belongs to which window. | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | ''Hints:'' | ||
+ | *This task belongs to the chapter [[Signal_Representation/Spectrum_Analysis|Spectrum Analysis]]. | ||
+ | *Note that the frequency resolution $f_{\rm A}$ is equal to the reciprocal of the adjustable parameter $T_{\rm P}$. | ||
+ | *Unfortunately, the indices of $f_{\rm A}$ and $Y_{\rm A}(f)$ collide. It is obvious that they are not related. Just to be on the safe side, we point this out. | ||
+ | |||
+ | |||
− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Which of the following statements are true with certainty when the DFT displays the output spectrum $Y_{\rm A}(f)$ ? |
|type="[]"} | |type="[]"} | ||
− | + | + | + The rectangular window was used for weighting. |
− | - | + | - The Hanning window was used for weighting. |
− | - | + | - The DFT parameter $T_{\rm P} = 4\ \text{ms}$ was used. |
− | + | + | + The DFT spectrum $Y_{\rm A}(f)$ is identical to the actual spectrum $X(f)$. |
− | { | + | {Using the Hanning window and $T_{\rm P} = 8 \ \text{ms} $, what is $Y(f)$ when the input spectrum $X(f) = Y_{\rm A}(f)$ is applied? <br>Give the weights of the Dirac delta lines at $f_1= 1\ \text{kHz}$ ⇒ $G(f_1)$ and at $f_2 = 1.125\ \text{kHz}$ ⇒ $G(f_2)$. |
|type="{}"} | |type="{}"} | ||
− | $G(f_1 = 1 \text{kHz}) =$ { 0.625 3% } V | + | $G(f_1 = 1.000 \ \text{kHz})\ = \ $ { 0.625 3% } $\text{V}$ |
− | $G( | + | $G(f_2 = 1.125 \ \text{kHz})\ = \ $ { 0.5 3% } $\text{V}$ |
− | { | + | {We consider the $1\ \text{kHz}$ cosine signal $x(t)$. Which spectrum - $Y_{\rm B}(f)$ or $Y_{\rm C}(f)$ – results with the rectangular or the Hanning window, respectively, if the DFT parameter $T_{\rm P} = 8.5 \ \text{ms}$ is chosen unfavourably? |
− | |type=" | + | |type="()"} |
− | - | + | - $Y_{\rm B}(f)$ results with rectangular windowing. |
− | + | + | + $Y_{\rm B}(f)$ results with the Hanning window. |
</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''1 | + | '''(1)''' <u>Solutions 1 and 4</u> are correct: |
− | + | *Using the Hanning window, three Dirac functions should be recognisable even if $x(t)$ contains only one frequency ⇒ the rectangular window was used. | |
− | + | *With $T_{\rm P} = 4 \ \text{ms}$ , the frequency resolution is $f_{\rm A}= 1/T_{\rm P} = 0.25 \ \text{kHz}$. Thus the frequency $f_2$ does not lie in the given grid and $Y(f)$ would be composed of very many Dirac delta lines. This means: the third statement is wrong. | |
+ | [[File:P_ID1167__Sig_A_5_4a.png|right|frame|Output signal $y(t)$ with the rectangular window]] | ||
− | + | *As can be seen from the graph, $x(t)$ has the period duration $T_{\rm 0} = 8 \ \text{ms}$. | |
+ | *If one chooses the DFT parameter equal to $T_{\rm P} = 4 \ \text{ms}$ (or an integer multiple thereof), the periodic continuation ${\rm P}\{ x(t)\} $ in the interval $|t| \leq T_{\rm P}/2$ coincides with $x(t)$ , so that the weighting function $w(t)$ has no disturbing effect. So: | ||
+ | *The DFT spectrum $Y(f)$ thus agrees with the actual spectrum. | ||
− | '''2 | + | |
+ | |||
+ | '''(2)''' Because of $T_{\rm 0} = 8 \ \text{ms}$ , the Hanning spectrum $W(f)$ | ||
+ | *consists of three Dirac functions at positive frequencies | ||
+ | *and three axisymmetrical Diracs at negative frequencies | ||
+ | |||
+ | |||
+ | are composed. For the positive frequencies, the spectral function is: | ||
+ | [[File:P_ID1169__Sig_A_5_4b.png|right|frame|Output signal $y(t)$ with the Hanning window]] | ||
− | $$W(f) =0.5\cdot {\rm \delta}(f) + 0.25\cdot {\rm \delta}(f-f_{\rm A})+ 0.25\cdot {\rm \delta}(f+f_{\rm A})\hspace{0.05cm}.$$ | + | :$$W(f) =0.5\cdot {\rm \delta}(f) + 0.25\cdot {\rm \delta}(f-f_{\rm A})+ 0.25\cdot {\rm \delta}(f+f_{\rm A})\hspace{0.05cm}.$$ |
− | + | The output spectrum results from the convolution between $X(f)$ and $W(f)$. At positive frequencies, there are now four Diracs with the following weights: | |
− | $$G(f = 0.875\,{\rm kHz}) & = | + | :$$\begin{align*} G(f = 0.875\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.25 = 0.250\, {\rm |
V}, \\ | V}, \\ | ||
− | G(f = f_1 = 1.000\,{\rm kHz}) & = | + | G(f = f_1 = 1.000\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.5 + 0.5\, {\rm V}\cdot 0.25 \hspace{0.15 cm}\underline{ = 0.625\, {\rm |
V}}, \\ | V}}, \\ | ||
− | G(f = f_2 = 1.125\,{\rm kHz}) & = | + | G(f = f_2 = 1.125\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.25 + 0.5\, {\rm V}\cdot 0.5 \hspace{0.15 cm}\underline{= 0.500\, {\rm |
V}}, \\ | V}}, \\ | ||
− | G(f = 1.250\,{\rm kHz}) & = | + | G(f = 1.250\,{\rm kHz}) & = 0.5\, {\rm V}\cdot 0.25 = 0.125\, {\rm |
V} | V} | ||
− | \hspace{0.05cm}.$$ | + | \hspace{0.05cm}.\end{align*}$$ |
− | + | The graph shows the attenuation of the edges by the weighting function $w(t)$ of the Hanning window. | |
− | |||
− | '''3 | + | '''(3)''' <u> Solution 2</u> is correct: |
+ | *The rectangular window delivers a very strongly distorted result if the window width $T_{\rm P}$ (as here) is not adapted to the cosine frequency. | ||
+ | *In this case, the Hanning window is more suitable. Then the measured spectrum $Y_{\rm B}(f)$ results. | ||
+ | * From the spectrum $Y_{\rm C}(f)$ the searched $1\ \rm kHz$ line is more difficult to detect. The spectrum $Y_{\rm C}(f)$ results after rectangular windowing. | ||
{{ML-Fuß}} | {{ML-Fuß}} | ||
__NOEDITSECTION__ | __NOEDITSECTION__ | ||
− | [[Category: | + | [[Category:Signal Representation: Exercises|^5.4 Spectrum Analysis^]] |
Latest revision as of 14:24, 18 January 2023
Let the time course of a periodic signal be given in principle:
- $$x(t) = A_1 \cdot \cos (2 \pi \cdot f_1 \cdot t) + A_2 \cdot \cos (2 \pi \cdot f_2 \cdot t) \hspace{0.05cm}.$$
Unknown and thus to be estimated are its parameters $A_1$, $f_1$, $A_2$ and $f_2$.
After weighting the signal with the window function $w(t)$ , the product $y(t) = x(t) \cdot w(t)$ is subjected to a Discrete Fourier Transform (DFT) with the parameters $N = 512$ and $T_{\rm P}$. The time $T_{\rm P}$ of the signal section to be analyzed can be set by the user as desired.
Two functions are available for windowing, each of which is zero for $|t| > T_{\rm P}/2$:
- The rectangular window:
- $${w} (\nu) = \left\{ \begin{array}{c} 1 \\ 0 \\ \end{array} \right.\quad \begin{array}{*{10}c} {\rm{for}} \\ \\ \end{array}\begin{array}{*{20}c} -N/2 \le \nu < N/2 \hspace{0.05cm}, \\ {\rm else} \hspace{0.05cm}, \\ \end{array}$$
- $$W(f) ={1}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot {f}/{f_{\rm A}})\hspace{0.05cm},$$
- the Hanning window:
- $${w} (\nu) = \left\{ \begin{array}{c} 0.5 + 0.5 \cdot \cos (2 \pi \cdot {\nu}/{N}) \\ 0 \\ \end{array} \right.\quad \begin{array}{*{10}c} {\rm{for}} \\ \\ \end{array}\begin{array}{*{20}c} -N/2 \le \nu < N/2 \hspace{0.05cm}, \\ {\rm else} \hspace{0.05cm}, \\ \end{array}$$
- $$W(f) ={0.5}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot \frac{f}{f_{\rm A}})+ {0.25}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot \frac{f-f_{\rm A}}{f_{\rm A}})+ {0.5}/{f_{\rm A}}\cdot {\rm si}(\pi \cdot \frac{f+f_{\rm A}}{f_{\rm A}})\hspace{0.05cm}.$$
Here, $W(f)$ is the Fourier transform of the continuous-time window function $w(t)$, while $w(ν)$ indicates the discrete-time weighting function.
In the task, reference is made to various spectral functions $Y(f)$ for example to
- $$Y_{\rm A}(f) = 1\, {\rm V}\cdot {\rm \delta} (f \pm 1\,\,{\rm kHz})+ 0.5\,\, {\rm V}\cdot {\rm \delta} (f \pm 1.125\,\,{\rm kHz}) \hspace{0.05cm}.$$
In the graph, two further spectral functions $Y_{\rm B}(f)$ and $Y_{\rm C}(f)$ are shown, which result when a $1 \ \text{kHz}$ signal is analyzed by DFT and the DFT parameter $T_{\rm P} = 8.5 \ \text{ms}$ is chosen unfavourably.
- For one of the images the rectangular window is used, for the other the Hanning window.
- It is not indicated which graph belongs to which window.
Hints:
- This task belongs to the chapter Spectrum Analysis.
- Note that the frequency resolution $f_{\rm A}$ is equal to the reciprocal of the adjustable parameter $T_{\rm P}$.
- Unfortunately, the indices of $f_{\rm A}$ and $Y_{\rm A}(f)$ collide. It is obvious that they are not related. Just to be on the safe side, we point this out.
Questions
Solution
- Using the Hanning window, three Dirac functions should be recognisable even if $x(t)$ contains only one frequency ⇒ the rectangular window was used.
- With $T_{\rm P} = 4 \ \text{ms}$ , the frequency resolution is $f_{\rm A}= 1/T_{\rm P} = 0.25 \ \text{kHz}$. Thus the frequency $f_2$ does not lie in the given grid and $Y(f)$ would be composed of very many Dirac delta lines. This means: the third statement is wrong.
- As can be seen from the graph, $x(t)$ has the period duration $T_{\rm 0} = 8 \ \text{ms}$.
- If one chooses the DFT parameter equal to $T_{\rm P} = 4 \ \text{ms}$ (or an integer multiple thereof), the periodic continuation ${\rm P}\{ x(t)\} $ in the interval $|t| \leq T_{\rm P}/2$ coincides with $x(t)$ , so that the weighting function $w(t)$ has no disturbing effect. So:
- The DFT spectrum $Y(f)$ thus agrees with the actual spectrum.
(2) Because of $T_{\rm 0} = 8 \ \text{ms}$ , the Hanning spectrum $W(f)$
- consists of three Dirac functions at positive frequencies
- and three axisymmetrical Diracs at negative frequencies
are composed. For the positive frequencies, the spectral function is:
- $$W(f) =0.5\cdot {\rm \delta}(f) + 0.25\cdot {\rm \delta}(f-f_{\rm A})+ 0.25\cdot {\rm \delta}(f+f_{\rm A})\hspace{0.05cm}.$$
The output spectrum results from the convolution between $X(f)$ and $W(f)$. At positive frequencies, there are now four Diracs with the following weights:
- $$\begin{align*} G(f = 0.875\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.25 = 0.250\, {\rm V}, \\ G(f = f_1 = 1.000\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.5 + 0.5\, {\rm V}\cdot 0.25 \hspace{0.15 cm}\underline{ = 0.625\, {\rm V}}, \\ G(f = f_2 = 1.125\,{\rm kHz}) & = 1\, {\rm V}\cdot 0.25 + 0.5\, {\rm V}\cdot 0.5 \hspace{0.15 cm}\underline{= 0.500\, {\rm V}}, \\ G(f = 1.250\,{\rm kHz}) & = 0.5\, {\rm V}\cdot 0.25 = 0.125\, {\rm V} \hspace{0.05cm}.\end{align*}$$
The graph shows the attenuation of the edges by the weighting function $w(t)$ of the Hanning window.
(3) Solution 2 is correct:
- The rectangular window delivers a very strongly distorted result if the window width $T_{\rm P}$ (as here) is not adapted to the cosine frequency.
- In this case, the Hanning window is more suitable. Then the measured spectrum $Y_{\rm B}(f)$ results.
- From the spectrum $Y_{\rm C}(f)$ the searched $1\ \rm kHz$ line is more difficult to detect. The spectrum $Y_{\rm C}(f)$ results after rectangular windowing.