Fourier Transform Time Shifting Property

In summary, The person was trying to find the Fourier Transform of a sine function with a time delay using two different methods. They noticed that they were getting two similar but not identical answers. They then asked for further explanation and clarified that they were familiar with the Dirac Delta function and its properties. After further discussion, they understood that it didn't matter if they used f or f0 in their calculations since both resulted in the same answer due to the multiplication with an impulse at f=f0. They expressed gratitude for the help provided.
  • #1
frenzal_dude
77
0

Homework Statement



I tried to work out the FT of a sin function with a time delay using first mathematical manipulation, and then using the time shifting property.

However I get two very similar, but for some reason not identical answers.

Homework Equations



Please open the .jpg to see my working out.
The answers are identical except for the 'f' and 'f0' which are circled in red pen.

The Attempt at a Solution



Thanks for your help!
 

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  • #2
It follows from the fact that [itex]f(x)\delta(x-x_0) = f(x_0)\delta(x-x_0)[/itex].
 
  • #3
vela said:
It follows from the fact that [itex]f(x)\delta(x-x_0) = f(x_0)\delta(x-x_0)[/itex].

could you please explain further?
 
  • #4
frenzal_dude said:
could you please explain further?
Are you familiar with the Dirac Delta function and its properties?
 
  • #5
Hootenanny said:
Are you familiar with the Dirac Delta function and its properties?

Yeh I am. And I understand the equation given. But where is that happening in my working out?

The exponential with f0 and t0 given is simply a complex number, and can't be considered a dirac delta function in the frequency domain right?
 
  • #6
What do you get if you apply that property to, say, [itex]e^{j2\pi f t_0} \delta(f-f_0)[/itex] (where [itex]e^{j2\pi f t_0}[/itex] is the function multiplying the delta function)?
 
  • #7
vela said:
What do you get if you apply that property to, say, [itex]e^{j2\pi f t_0} \delta(f-f_0)[/itex] (where [itex]e^{j2\pi f t_0}[/itex] is the function multiplying the delta function)?

I fully get it now!

Basically it doesn't matter if you use f or f0, the result is the same since you are multiplying with an impulse at f=f0!

Thanks so much for your help!
 

Related to Fourier Transform Time Shifting Property

1. What is the Fourier Transform Time Shifting Property?

The Fourier Transform Time Shifting Property is a mathematical property that describes how shifting a signal in the time domain affects its Fourier Transform in the frequency domain.

2. How does the Fourier Transform Time Shifting Property work?

The Fourier Transform Time Shifting Property states that a time shift in the time domain results in a phase shift in the frequency domain. This means that the magnitude of the Fourier Transform remains the same, but the phase of each frequency component is shifted by the same amount as the time shift.

3. What is the significance of the Fourier Transform Time Shifting Property in signal processing?

The Fourier Transform Time Shifting Property is a fundamental property in signal processing and is used in a wide range of applications, including filtering, modulation, and digital signal processing. It allows us to analyze and manipulate signals in the frequency domain, which can be more efficient and accurate than working in the time domain.

4. Can the Fourier Transform Time Shifting Property be applied to both continuous and discrete signals?

Yes, the Fourier Transform Time Shifting Property applies to both continuous and discrete signals. In the case of continuous signals, the time shift is represented as a continuous function, while in the case of discrete signals, the time shift is represented as a discrete sequence.

5. Are there any limitations to the Fourier Transform Time Shifting Property?

The Fourier Transform Time Shifting Property assumes that the signal is infinite in duration and that the time shift is constant throughout the signal. In real-world applications, these assumptions may not hold true, and adjustments may need to be made for accurate analysis and manipulation of the signal.

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