Sketching Fourier Transform of Lowpass Filter with Time Delay and Bandwidth

In summary, the conversation discusses the impulse response of a unity-gain ideal lowpass filter with a bandwidth of 50Hz and a time delay of 5ms. The magnitude and phase of the Fourier transform of the impulse response are also discussed, with the magnitude being the total power gain and the phase graph showing a downward slope from -90 degrees to 0 degrees. The impact of a time delay on the frequency domain is also mentioned, as well as the relationship between convolution in the time domain and multiplication in the frequency domain.
  • #1
satchmo05
114
0

Homework Statement


Let h(t) be impulse response of unity-gain ideal lowpass filter with bandwidth of 50[Hz] and a time delay of 5[ms]. Sketch magnitude and phase of Fourier transform of h(t).

The Attempt at a Solution


I know that the magnitude2 of H(f) is total power gain, so perhaps by taking the square of this expression might get me the magnitude of simply H(f). However, I am not exactly sure how to take the information given to convert into an expression I can actually deal with.

Any help would be most appreciated. Thanks!
 
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  • #2
How does low pass filter frequency response looks like?

Now, you are making a shift in time domain, how would this impact in frequency domain?

In impulse response input is δ(t), so output will be: y(t) = δ(t) conv h(t). What would this equal in frequency domain? Y(s) = ?
 
  • #3
rootX,

Thank you for your response! I believe I understand the magnitude of the response. The magnitude is simply a function of the lowpass filter itself, drawing the bandwidth as given where the function's bandwidth breaks at the corner frequency (-3db). I do not believe the time delay affects a low pass filter. However, the phase graph may and that is where I am having trouble now. I believe the phase plot will look like a downward slope from -90 degrees to 0 degrees, where -45 degrees and 20[Hz] intersect.

If I introduce a time delay in the continuous time domain (h(t)), that would add a complex exponential factor in front of the H(f). Does this only change the order of magnitude of the two magnitude and phase plots?

If you convolve in the time domain, you multiply in the frequency domain. What did you mean by that statement? Thanks again for your help.
 

FAQ: Sketching Fourier Transform of Lowpass Filter with Time Delay and Bandwidth

What is a Fourier transform?

A Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It takes a function in the time domain and converts it into a function in the frequency domain.

Why is the Fourier transform important?

The Fourier transform is important because it allows us to analyze signals and data in the frequency domain, which can provide insights and information that may not be apparent in the time domain. It is widely used in fields such as signal processing, image processing, and data analysis.

How is a Fourier transform calculated?

The Fourier transform is calculated using an integral equation that involves the function being transformed and a complex exponential function. This integral equation is solved using techniques such as integration by parts and the properties of complex numbers.

What is the difference between a discrete and continuous Fourier transform?

A continuous Fourier transform is used for functions that are continuous and infinite, while a discrete Fourier transform is used for functions that are discrete and finite. The continuous Fourier transform involves an integral, while the discrete Fourier transform involves a sum.

Can a Fourier transform be reversed?

Yes, a Fourier transform can be reversed using an inverse Fourier transform. This operation converts a function in the frequency domain back into the time domain. It is important to note that the inverse Fourier transform may not produce the exact original function, but rather a scaled or shifted version of it.

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