Fourier Transform of a Modified Impulse Train

Click For Summary
SUMMARY

The discussion focuses on the Fourier Transform of a modified impulse train defined as x(t) = 2\hat{x}(t) + \hat{x}(t-1), where \hat{x}(t) = \sum_{k=-\infty}^{\infty}\delta(t-2k). The official solution provided by Oppenheim states that the Fourier Transform is X(jω) = π ∑ δ(ω - πk)[2 + (-1)^k]. Key questions arise regarding the application of the time-shifting property, specifically why e^{-ω} is used instead of e^{-jω}, and how e^{-jω} translates to (-1)^k in the final answer. The consensus is that the original solution contains a mistake regarding the time-shifting property.

PREREQUISITES
  • Understanding of Fourier Transform and its properties
  • Familiarity with delta functions and impulse trains
  • Knowledge of time-shifting in signal processing
  • Basic concepts of complex exponentials in frequency domain analysis
NEXT STEPS
  • Study the properties of the Fourier Transform, particularly time-shifting
  • Learn about delta functions and their role in signal processing
  • Explore the relationship between complex exponentials and trigonometric identities
  • Review Oppenheim's "Signals and Systems" for detailed examples and solutions
USEFUL FOR

Electrical engineers, signal processing students, and anyone interested in advanced Fourier analysis and its applications in systems theory.

WolfOfTheSteps
Messages
134
Reaction score
0
I hope this is OK to post here. I thought it would be better here than in the math questions forum, since you are EEs, and probably have more experience dealing with things related to the delta function.

Problem

Let

\hat{x}(t) = \sum_{k=-\infty}^{\infty}\delta(t-2k).

Now let

x(t) = 2\hat{x}(t) + \hat{x}(t-1).

Find the Fourier Transform of x(t).

Given Solution

Here is the official solution given by Oppenheim:

From Table 4.2,

\hat{X}(j\omega) = \pi \sum_{k=-\infty}^{\infty}\delta(\omega - \pi k)

Therefore,

X(j\omega)=\hat{X}(j\omega)[2+e^{-\omega}] = \pi \sum_{k=-\infty}^{\infty}\delta(\omega-\pi k)[2 + (-1)^k].

My Two Questions

Question 1. When applying the time-shifting property of Fourier series, why did they multiply by e^{-\omega} and not e^{-j\omega}??

Question 2. How did the e^{-\omega} become (-1)^k in the final answer?

Thank you!
 
Last edited:
Engineering news on Phys.org
WolfOfTheSteps said:
Question 1. When applying the time-shifting property of Fourier series, why did they multiply by e^{-\omega} and not e^{-j\omega}??

it's a mistake. i don't have the book, but if you represented this correctly, they are wrong and you are right. delaying by one sample multiplies the continuous spectrum by e^{-j\omega} . this will fix your Q2 also.
 
delaying by one sample multiplies the continuous spectrum by e^{-j\omega}. this will fix your Q2 also.

Maybe not! How does e^{-j\omega} become (-1)^k in the final answer? :biggrin: I know e^{-j k \pi} = (-1)^k but how could that come from e^{-j\omega} when omega is variable and there is no k? Is the final answer also a typo?

Thanks!
 
WolfOfTheSteps said:
Maybe not! How does e^{-j\omega} become (-1)^k in the final answer? :biggrin: I know e^{-j k \pi} = (-1)^k but how could that come from e^{-j\omega} when omega is variable and there is no k? Is the final answer also a typo?

Thanks!

Remember, you are multiplying the e^{-j \omega} by a chain of delta functions (in \omega-space). The only thing that matters is where the delta function is nonzero.

Remember f(x)\delta(x-a) = f(a)\delta(x-a)
 
mdelisio said:
Remember, you are multiplying the e^{-j \omega} by a chain of delta functions (in \omega-space). The only thing that matters is where the delta function is nonzero.

Of course! Which happens exactly when \omega = \pi k. I should have realized that! :rolleyes:

Thanks!
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 0 ·
Replies
0
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K