Signal & System CTFT: Find x(t) from X(ω)

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  • Thread starter hquang001
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In summary, the conversation discusses finding the CT signal x(t) associated with a given CTFT and using a table of FTs to find hints. The conversation also mentions trying a certain method that did not match the solution given by the professor.
  • #1
hquang001
31
3
Homework Statement
Find the CT signal associated with CTFT:
Relevant Equations
.
Given the CTFT X(ω): 1638042527872.png
1638042702750.png

and here are my solution to find CT signal x(t) associated with the given CTFT , but i got stuck at the limit part
 
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  • #2
  • #3
BvU said:
FInd any hints in a table of FTs ?

##\ ##
Oh, my professor never mention this, i will check this and see
Thank you
 
  • #4
##\exp(n(jt-1/2))-1\to -1## as ##n\to \infty## since ##\exp(jtn)=\cos(tn)+j\sin(tn)## and ##\exp(-n/2)\to 0## as ##n\to \infty##.
 
  • #5
MathematicalPhysicist said:
##\exp(n(jt-1/2))-1\to -1## as ##n\to \infty## since ##\exp(jtn)=\cos(tn)+j\sin(tn)## and ##\exp(-n/2)\to 0## as ##n\to \infty##.
Yes i have tried this before, but it didn't match the solution that my professor gave, that's why i ask in here to check
1638093425950.png
 

1. What is the purpose of finding x(t) from X(ω) in signal and system analysis?

The purpose of finding x(t) from X(ω) is to understand the relationship between a signal in the time domain and its representation in the frequency domain. This allows for the analysis and manipulation of signals using mathematical techniques in the frequency domain, which can be more efficient and intuitive than working in the time domain.

2. How do you find x(t) from X(ω) in signal and system analysis?

To find x(t) from X(ω), you can use the inverse continuous-time Fourier transform (CTFT) formula: x(t) = ∫X(ω)e^(jωt)dω, where X(ω) is the frequency domain representation of the signal and x(t) is the time domain representation. This formula can be calculated using calculus or by using tables of common transforms.

3. What is the difference between continuous-time Fourier transform (CTFT) and discrete-time Fourier transform (DTFT)?

The continuous-time Fourier transform (CTFT) is used to analyze signals that are continuous in time, while the discrete-time Fourier transform (DTFT) is used for signals that are discrete in time. The CTFT uses continuous variables (such as frequency ω) while the DTFT uses discrete variables (such as frequency in radians/sample). The inverse transforms for CTFT and DTFT also differ in their formulas.

4. Can you find x(t) from X(ω) for any signal?

In theory, yes, you can find x(t) from X(ω) for any signal using the inverse CTFT formula. However, in practice, this may not always be possible due to the complexity of the signal or limitations in the analysis tools available. In some cases, it may be more practical to approximate the signal using a simpler function or to use other techniques for signal analysis.

5. How is finding x(t) from X(ω) useful in real-world applications?

Finding x(t) from X(ω) is useful in many real-world applications, such as in signal processing, telecommunications, and audio and image processing. It allows for the analysis and manipulation of signals in the frequency domain, which can be more efficient and intuitive than working in the time domain. This can lead to improved signal quality, increased data transmission rates, and more efficient data storage and compression techniques.

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