Matching Discrete Fourier Transform (DFT) Pairs

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Homework Help Overview

The discussion revolves around matching discrete-time signals with their corresponding Discrete Fourier Transforms (DFTs). The context involves analyzing 28-point signals and understanding the implications of sampling rates and signal characteristics on their frequency representations.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the relationship between sampling rates and the appearance of frequency peaks in the DFTs. Questions arise about the interpretation of signals that resemble rectangular pulses and how their average values affect DFT matching.

Discussion Status

Participants are actively engaging with the problem, questioning assumptions about frequency representation and sampling effects. Some guidance has been offered regarding the relationship between signal duration and frequency range, though there is no explicit consensus on the final matching of signals to DFTs.

Contextual Notes

There are references to previous threads that may provide additional context, and participants note the lack of labeled axes on the DFTs as a constraint in their analysis. The discussion includes considerations of how the characteristics of the signals influence their DFTs.

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Homework Statement


[/B]
I am trying to match each of the following 28-point discrete-time signals with its DFT:

Set #1:

DFTmatching.png


Set #2:

dftset2.png


Homework Equations

The Attempt at a Solution



Set #1
We have already established (here) that:

##Signal 1 \leftrightarrow DFT3##
##Signal 4 \leftrightarrow DFT2##

Now, Signal 3 looks like Signal 4. The only difference is that the temporal sample spacing has been increased. So, instead of having a single central peak in the DFT, we now have two peaks (at 7 and 21). Why?

Likewise, Signal 2 looks like Signal 1, except it was sampled at twice the sampling interval. So, why does increasing the sample spacing create an additional frequency peak in each case? :confused:

Set #2:
These signals look like rectangular pulses (but none of them are a full period of a periodic rectangular signal). The DFT of a rectangular pulse is samples of the sinc function. DFT1 & 3 look like sincs, but I am not sure how to interpret DFT2.

Clearly, each signal has a different average value. For instance, Signal 3 should have the highest DC value because it has more samples at 1 than the other two signals. But the axes of the DFTs are not labeled. So, how else can I match these?

Any suggestions would be greatly appreciated.
 
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roam said:
Now, Signal 3 looks like Signal 4. The only difference is that the temporal sample spacing has been increased. So, instead of having a single central peak in the DFT, we now have two peaks (at 7 and 21). Why?

Likewise, Signal 2 looks like Signal 1, except it was sampled at twice the sampling interval. So, why does increasing the sample spacing create an additional frequency peak in each case? :confused:
Is there really an additional frequency? Think about it. What is special about the sampling rate for signals 1 and 4?

roam said:
Set #2:
These signals look like rectangular pulses (but none of them are a full period of a periodic rectangular signal). The DFT of a rectangular pulse is samples of the sinc function. DFT1 & 3 look like sincs, but I am not sure how to interpret DFT2.
Going back to the previous thread, think about how these signals fit in with respect to signals 1 and 6 in that problem.
 
DrClaude said:
Is there really an additional frequency? Think about it. What is special about the sampling rate for signals 1 and 4?

In direct space, the period is 2. For instance, we can see that in signal 4, it is the largest frequency to represent a cosine with. Signal 3 looks like another cosine oscillating at a slower frequency. Where does the additional frequency come from?

Going back to the previous thread, think about how these signals fit in with respect to signals 1 and 6 in that problem.

Could you please explain more? I don't see how it relates to this problem.

Signal 1 & 6 in that problem show that a constant function corresponds to a Dirac-##\delta## spectrum, and conversely a ##\delta## impulse corresponds to a constant.

I also know this relationship between sample spacing and span in each domain:

$$\begin{array}{c|cc}
& \text{Time} & \text{Freq}\\
\hline \text{Spacing} & \Delta T & 1/N\Delta T\\
\text{Span} & N\Delta T & 1/\Delta T
\end{array}$$
 
roam said:
In direct space, the speriod is 2. For instance, we can see that in signal 4, it is the largest frequency to represent a cosine with. Signal 3 looks like another cosine oscillating at a slower frequency. Where does the additional frequency come from?
I'll ask again: are there really two frequencies? (Think about the ordering of the DFT, as per the previous thread.)
roam said:
Could you please explain more? I don't see how it relates to this problem.
What is the relation between the length of a signal in time and the width of its frequency spectrum?
 
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DrClaude said:
I'll ask again: are there really two frequencies? (Think about the ordering of the DFT, as per the previous thread.)

Thank you. So the highest frequency is in the center, so in DFT2 and DFT3 the two DFT coefficients overlap.

What is the relation between the length of a signal in time and the width of its frequency spectrum?

They are inversely proportional. If the length of the temporal signal is ##\text{NT}## (where ##\text{T}## is the intersample spacing, and ##\text{N}## is the number of samples), then the length of the frequency spectrum is ##\text{1/T}##.

So basically more of the overall sinc function is contained in the DFT of the signal with a smaller period? Signals 1, 2, and 3 correspond to DFTs 3, 1, and 2 respectively?

But this can't be right because from my notes, for a full period of a rectangular pulse we have this pair:

pair.png


In our problem, Signal 3 looks most like the signal shown above. So its DFT should also look more like that (i.e. ##\text{Signal3} \leftrightarrow \text{DFT3}##).
 
roam said:
Thank you. So the highest frequency is in the center, so in DFT2 and DFT3 the two DFT coefficients overlap.
Correct. Since signals 2 and 3 correspond to half the frequency, the positive and negative components of the same absolute frequency now appear as separated.
roam said:
So basically more of the overall sinc function is contained in the DFT of the signal with a smaller period? Signals 1, 2, and 3 correspond to DFTs 3, 1, and 2 respectively?
That's not correct, and as you indicate, is not compatible with the other signal you have in your notes. The conclusion is that the shorter the duration of the rectangular pulse, the broader its frequency range is. Using that heuristic, can you now assign the DFT for signals 1, 2 and 3?
 
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DrClaude said:
That's not correct, and as you indicate, is not compatible with the other signal you have in your notes. The conclusion is that the shorter the duration of the rectangular pulse, the broader its frequency range is. Using that heuristic, can you now assign the DFT for signals 1, 2 and 3?

DFT2 has 1 zero, DFT1 has 3 zeros, DFT3 has 7 zeros. So, DFT2 is the broadest because there are more frequency components present in its spectrum?

In summary:
##\text{Signal 1} \leftrightarrow \text{DFT 2}##
##\text{Signal 2} \leftrightarrow \text{DFT 1}##
##\text{Signal 3} \leftrightarrow \text{DFT 3}##

Is that correct?
 
roam said:
In summary:
##\text{Signal 1} \leftrightarrow \text{DFT 2}##
##\text{Signal 2} \leftrightarrow \text{DFT 1}##
##\text{Signal 3} \leftrightarrow \text{DFT 3}##

Is that correct?
Yes.
 
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Thank you so much for your help. It makes perfect sense now.
 

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