Fourier transform vs Inner product

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SUMMARY

The discussion centers on the relationship between the Fourier transform and the inner product in the context of representing functions. It establishes that the complex exponential Fourier series forms an orthonormal basis for functions, with periodic functions requiring countably many elements and aperiodic functions necessitating uncountably many elements. The conversation highlights the similarity yet distinct nature of the Fourier transform and inner product methods for obtaining coefficients of complex exponentials, emphasizing the need for clarity regarding the conventions used in Fourier series versus Fourier transforms.

PREREQUISITES
  • Understanding of Fourier series and Fourier transforms
  • Knowledge of orthonormal bases in functional spaces
  • Familiarity with complex exponentials
  • Basic principles of signal representation
NEXT STEPS
  • Study the differences between Fourier series and Fourier transforms
  • Explore the concept of orthonormal bases in functional analysis
  • Learn how to compute Fourier coefficients using inner products
  • Investigate applications of Fourier transforms in signal processing
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Mathematicians, signal processing engineers, and students studying functional analysis or Fourier analysis will benefit from this discussion.

Bipolarity
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So the complex exponential Fourier series form an orthonormal basis for the space of functions. A periodic function can be represented with countably many elements from the basis, and an aperiodic function requires uncountably many elements.

Given a signal, we can find the coefficients of the exponentials in two ways:
1) Fourier transform
2) Inner product with that complex exponential

Though these two formulas are similar, they are not identical. So how could they both possibly give us the coefficient of a complex exponential?

Thanks!

BiP
 
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Can you please show the formulas you are comparing? There are several different conventions in use. Also, please clarify whether you are talking about Fourier series or Fourier transforms. You mentioned both.
 
[quotr]A periodic function can be represented with countably many elements from the basis, and an aperiodic function requires uncountably many elements.
[/quote]
What do have in mind? The basis has only a countable number of elements. Are you mixing Fourier series and Fourier transdforms?
 
an aperiodic function requires uncountably many elements.
But not necessarily uncountably many non-zero elements. For example ##\cos t + \cos \pi t##.

But I agree with the other posters, it's hard to figure out exactly what your OP is asking.
 

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