How to find Fourier Transform of pulse and apply it on filter response?

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SUMMARY

This discussion focuses on determining the Fourier Transform of a temporal pulse to analyze the output of a known filter characterized by its amplitude and phase response in terms of frequency (ω). The user has calculated the filter's response numerically for discrete ω values and seeks to apply this to the Fourier Transform of a pulse, represented as summation(A(ω)exp(iωt)). The output can be expressed as summation(A(ω)H(ω)exp(iωt), where H(ω) is the filter's response. Key insights include modeling the transfer function using poles and zeros and the relationship between convolution in the time domain and multiplication in the frequency domain.

PREREQUISITES
  • Understanding of Fourier Transform and its mathematical representation.
  • Familiarity with filter design and transfer functions.
  • Knowledge of amplitude and phase response in signal processing.
  • Basic concepts of poles and zeros in control theory.
NEXT STEPS
  • Learn how to compute the Fourier Transform of various pulse shapes.
  • Study the application of poles and zeros in filter design and analysis.
  • Explore convolution theorem and its implications in signal processing.
  • Investigate numerical methods for calculating discrete Fourier Transforms.
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Signal processing engineers, control system designers, and anyone involved in analyzing filter responses and applying Fourier Transforms to time-domain signals.

russel.arnold
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Hi all,

I have a filter whose amplitude and phase response in terms of w(omega) is known to me which i calculated numerically. Hence, the value is known only for discrete values of w(omega).

Now, I want to know the output which this filter will produce on sending a temporal pulse(pulse in time domain) as my input.

I know i need to Fourier transform my pulse( in the form summation(A(w)exp(iwt)) and then write the output as something like summation(A(w)*H(w)*exp(jwt)).

The question is how can i find the Fourier transform (i.e find A(w) at those w where response of filter is known)
 
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russel.arnold said:
Hi all,

I have a filter whose amplitude and phase response in terms of w(omega) is known to me which i calculated numerically. Hence, the value is known only for discrete values of w(omega).

Now, I want to know the output which this filter will produce on sending a temporal pulse(pulse in time domain) as my input.

I know i need to Fourier transform my pulse( in the form summation(A(w)exp(iwt)) and then write the output as something like summation(A(w)*H(w)*exp(jwt)).

The question is how can i find the Fourier transform (i.e find A(w) at those w where response of filter is known)

Usually you model the transfer function as a polynomial of poles and zeros. You know the DC gain and you see that whenever the transferfunction slope changes +-20 dB/decade that you have a pole or zero at that place.

Edit: I think this is more commonly done in the laplace domain than in the Fourier domain.
 
russel.arnold said:
Hi all,

I have a filter whose amplitude and phase response in terms of w(omega) is known to me which i calculated numerically. Hence, the value is known only for discrete values of w(omega).

Now, I want to know the output which this filter will produce on sending a temporal pulse(pulse in time domain) as my input.

I know i need to Fourier transform my pulse( in the form summation(A(w)exp(iwt)) and then write the output as something like summation(A(w)*H(w)*exp(jwt)).

The question is how can i find the Fourier transform (i.e find A(w) at those w where response of filter is known)

Well, since you have a filter whose amplitude and phase response in terms of w(omega) is known you can use those discrete values to determine the increment in which they are increasing/decreasing at... although I am not exactly sure how you have these values/the manner in which you calculated them.

When you transform your pulse (you never directly mentioned what kind) yielding a 'continuous' waveform, simply plug that incrementing discrete values of frequency in it. Remember, convolution in the Time Domain is multiplication in the Frequency Domain.
 

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