Convolution - Fourier Transform

In summary: When you do this, you will see that the ## \delta(t) ## response and the ## u(t) ## response are different. the ## \delta(t) ## response is the transient response, and the ## u(t) ## response is the steady-state response. I've read that before, but it's been a while. This is a good problem.In summary, the given LTI system has an impulse response of h(t) = e^-|t| and an input of x(t) = ejΩt. The system output can be found using convolution and the dominant frequency and maximum value of y(t) can be found. To solve this problem, one must use
  • #1
Jonski
42
0

Homework Statement


An LTI system has an impulse response h(t) = e-|t|
and input of x(t) = ejΩt

Homework Equations


Find y(t) the system output using convolution
Find the dominant frequency and maximum value of y(t)
Ω = 2rad/s

The Attempt at a Solution


I have tried using the Fourier transform to get y(t) but when you try to find X(Ω), I get infinity
as X(Ω) = ∫ x(t) * e-jΩtdt = ∫ e jΩt*e-jΩtdt = ∫ 1 dt = t between inf and -inf
h(t) I could find as 2/(1+Ω2)

Any ideas on how to solve this?
 
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  • #2
You need to write the transform as ## X(\omega)=\int x(t) e^{-i \omega t} dt ##. The result is ## X(\omega)=2 \pi \, \delta(\omega-\Omega) ##. You need to read about delta functions. If you google it, you should find some useful formulas like the one I just gave you.
 
  • #3
Charles Link said:
You need to write the transform as ## X(\omega)=\int x(t) e^{-i \omega t} dt ##. The result is ## X(\omega)=2 \pi \, \delta(\omega-\Omega) ##. You need to read about delta functions. If you google it, you should find some useful formulas like the one I just gave you.
So then using that you would get that Y(w) = 4π/(1+w2) * δ(w-2), but then how would you get that back into the time domain?
 
  • #4
## H(\omega)=\int\limits_{0}^{+\infty} h(t) e^{-i \omega t} dt ##, since ## h(t)=0 ## for ## t<0 ##. (Perhaps they didn't tell you this (## h(t)=0 ## for ## t<0 ##) in the problem statement, but it is clear that that's what they want). Try recomputing ## H(\omega) ##.(You have it incorrect). ## \\ ## Now ## Y(\omega)=H(\omega)X(\omega) ##. (That part you have correct.) ## \\ ## Use an inverse transform to get ## y(t)=\frac{1}{2 \pi} \int\limits_{-\infty}^{+\infty} Y(\omega) e^{i \omega t} \, d \omega ##. ## \\ ## Wait until you process everything to put in the value for ## \Omega ##.
 
  • #5
Charles Link said:
## H(\omega)=\int\limits_{0}^{+\infty} h(t) e^{-i \omega t} dt ##, since ## h(t)=0 ## for ## t<0 ##. Try recomputing ## H(\omega) ##.(You have it incorrect). ## \\ ## Now ## Y(\omega)=H(\omega)X(\omega) ##. (That part you have correct.) ## \\ ## Use an inverse transform to get ## y(t)=\frac{1}{2 \pi} \int\limits_{-\infty}^{+\infty} Y(\omega) e^{i \omega t} \, d \omega ##. ## \\ ## Wait until you process everything to put in the value for ## \Omega ##.
Sorry the reason why I got what i did for H(w), was because I forget to put in an absolute around the t. I've changed in now
 
  • #6
Jonski said:
Sorry the reason why I got what i did for H(w), was because I forget to put in an absolute around the t. I've changed in now
An ## h(t) ## with an absolute value would be unphysical. That is saying it responds before the impulse. These functions always begin at ## t=0 ##. If they gave you the problem in such a fashion, it is unphysical.
 
  • #7
Incidentally, if ## H(t) ## is the response to a unit step function, ## h(t)=\frac{dH(t)}{dt} ## is the response to the delta function. The problem they gave you, if I'm not mistaken, is basically a series R-C circuit (along with an input voltage source) with the output voltage being measured across the capacitor, and the product ## RC=1 ##, because of the form ## h(t)=e^{-t} ##. ## \\ ## Let the input voltage source be a unit step function, and/or a delta function, and you can compute the ## h(t) ## that they give you., i.e. for the R-C circuit, with ## RC=1 ##, when ## V_{in} (t)=\delta(t) ##, you get ## V_C(t)=e^{-t} ## for ## t>0 ## . Try and see. I believe I have this result correct. ## \\ ## And additional item: If you are familiar with ac circuit analysis, try comparing the result that you get from the linear response theory with that from computing the ac impedances of the two components and considering it as a voltage divider problem-i.e. the ac voltage across the capacitor is readily computed.
 
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1. What is the difference between convolution and Fourier transform?

Convolution is a mathematical operation that combines two functions to produce a third function. It is used to represent the output of a linear system given its input. Fourier transform, on the other hand, is a mathematical tool that decomposes a function into its constituent frequencies. It is used to analyze signals and systems in the frequency domain.

2. How is convolution used in signal processing?

Convolution is used in signal processing to model the output of a linear system given its input. It allows us to analyze how a signal is affected by a system, such as a filter or amplifier. It is also used in image processing to apply filters or blurring effects to images.

3. What is the mathematical formula for convolution?

The mathematical formula for convolution is f(x) * g(x) = ∫f(t)g(x-t)dt, where f(x) and g(x) are the two functions being convolved, and * represents the convolution operation.

4. How does the Fourier transform relate to convolution?

The Fourier transform of a convolution of two functions is equal to the product of their individual Fourier transforms. This property is known as the convolution theorem and is used to simplify the analysis of linear systems in the frequency domain.

5. What are some real-world applications of convolution and Fourier transform?

Convolution and Fourier transform have various real-world applications, including signal and image processing, audio and video compression, and pattern recognition. They are also used in fields such as physics, engineering, and economics for data analysis and modeling.

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