Peak of Analytical Fourier Transform

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SUMMARY

The discussion centers on the analytical Fourier transform of the function ##\sin\Omega t##, which yields a Fourier transform represented by the Dirac delta functions $$-i\pi\delta(\Omega-\omega)+i\pi\delta(\omega+\Omega)$$. It is established that differentiating the Dirac delta function to find the peak frequency is not applicable due to its nature as a distribution. The peak frequency corresponds to ##\Omega##, and while traditional methods of differentiation are not valid here, it is noted that tools like Matlab can be employed to analyze maxima and minima of Fourier transforms effectively.

PREREQUISITES
  • Understanding of Fourier transforms, particularly analytical Fourier transforms.
  • Familiarity with Dirac delta functions and their properties.
  • Basic knowledge of numerical methods for function optimization.
  • Experience with Matlab for numerical analysis and visualization.
NEXT STEPS
  • Explore the properties and applications of Dirac delta functions in signal processing.
  • Learn how to implement Fourier transforms in Matlab for various functions.
  • Study the differences between analytical and numerical Fourier transforms.
  • Investigate optimization techniques for finding maxima and minima in mathematical functions.
USEFUL FOR

Mathematicians, signal processing engineers, and anyone involved in analytical methods for Fourier transforms will benefit from this discussion.

Luke Tan
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TL;DR
Finding the peak frequency in an analytical fourier transform
In a numerical Fourier transform, we find the frequency that maximizes the value of the Fourier transform.

However, let us consider an analytical Fourier transform, of ##\sin\Omega t##. It's Fourier transform is given by
$$-i\pi\delta(\Omega-\omega)+i\pi\delta(\omega+\Omega)$$
Normally, to find the value of ##\omega## that maximizes this function, we would differentiate with respect to ##\omega## and set to 0. However, in this case, the derivative of a dirac delta function cannot be evaluated. Hence, we are unable to find the peak frequency to be at ##\Omega## unlike what we would in a numerical, discrete-time Fourier transform.

Is there any way around this, to find the peak frequency of the Fourier transform of a function?
 
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Te Dirac delta is 0 everywhere except for ##\delta(0) \neq 0##. It shouldn't be too har to find where the FT has a peak :smile:
 
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DrClaude said:
Te Dirac delta is 0 everywhere except for ##\delta(0) \neq 0##. It shouldn't be too har to find where the FT has a peak :smile:
oh so this is a special case, and does not disqualify differentiating and setting to 0 as a general method of finding the peak frequency?
 
Luke Tan said:
oh so this is a special case, and does not disqualify differentiating and setting to 0 as a general method of finding the peak frequency?
Yes, it's a special case because the Dirac delta is not a real function, but a distribution, so you can't apply the same methods as you would normally use.
 
What frequency is the sine wave oscillating at? That is where your delta function will be and at ##2 \pi - \Omega##

You could always use Matlab or etc. to find maxes and mins of Fourier's.
 

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