Why Does Inverse Fourier Transform of Sinc Function Require Contour Integration?

In summary, there is a discrepancy when attempting to inverse Fourier transform the sinc function, leading to the use of contour integration and Cauchy principal values. This suggests that the usual definition of a Fourier transform may be inadequate in certain cases and could lead to incorrect results. The author suggests that the appropriate type of improper integral to use is the Cauchy Principal Value, as it takes into account the periodic nature of Fourier transforms and considers an approximation of the sinc function with finite boundaries.
  • #1
bdforbes
152
0
I can easily find the Fourier transform of rect(x) to be [itex]2sinc(2\pi k)[/itex] using particular conventions (irrelevant here). But when I attempt to inverse Fourier transform the sinc function, I find I have to resort to contour integration and Cauchy principal values.

This is troubling to me. It appears as if the usual definition of a Fourier transform is inadequate here, and could possibly lead to incorrect results in another context. Can anyone shed any light on this?
 
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  • #2
I have come to the conclusion that the Cauchy Principal Value is the appropriate type of improper integral to use. This is because Fourier transforms originate in the consideration of periodic functions; we should consider some approximation to the sinc function which is periodic, i.e. cut the function off at some finite symmetric boundary, take the Fourier transform, and then take the limits symmetrically to infinity.
 

Related to Why Does Inverse Fourier Transform of Sinc Function Require Contour Integration?

1. What is the Fourier transform?

The Fourier transform is a mathematical tool used to decompose a function into its constituent frequencies. It allows us to analyze the frequency components of a signal or function.

2. What is the Fourier transform of a rectangular function?

The Fourier transform of a rectangular function (rect(x)) is a sinc function, which is defined as sin(x)/x. It has a main lobe at the center and smaller lobes on either side, with the height and width of the lobes determined by the width of the rectangular function.

3. What is the significance of the Fourier transform of rect(x)?

The Fourier transform of rect(x) is used to model signals with finite duration, such as square waves, rectangular pulses, and boxcar functions. It is also used in signal processing and image analysis to remove noise and extract important frequency components.

4. Can the Fourier transform be applied to all functions?

Technically, the Fourier transform can be applied to any function, but it is most useful for functions that are well-behaved and have a finite duration. For functions with infinite duration, the Fourier transform is not well-defined.

5. How is the Fourier transform of rect(x) calculated?

The Fourier transform of rect(x) can be calculated using the formula F(ω) = sinc(ω/2π), where ω is the frequency and sinc(x) = sin(x)/x. This can also be written as F(ω) = ∫rect(x)e^(-iωx)dx, where rect(x) is the rectangular function and e^(-iωx) is the complex exponential function.

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