Exploring Fourier Transforms and Integrability for Different Functions

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In summary, the conversation discusses proving that the function f(x) = (1 + |x|)^{-a} is the Fourier transform of an integrable function on R when a > 1. It is mentioned that when 0 < a <= 1, the integral may not converge when taking the inverse transform. The function f(x) = 1/(log(|x|^2 + 2)) is also brought up, with the question of whether or not it is the Fourier transform of an integrable function. The conversation then moves on to discussing a possible argument for why the denominator in the function needs to have a power greater than 1 in order for the integral to converge. However, the speaker is unsure about how to
  • #1
shoplifter
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prove that f(x) = (1 + |x|)^{-a} is the Fourier transform of some integrable function on R, when a > 1. what happens when 0 < a <= 1? how about the function f(x) = 1/(log(|x|^2 + 2))?
 
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  • #2
Is this homework? If so, what have you done so far?
 
  • #3
yes, and i realize that we want the integral to converge when we take the inverse transform. so in order to do that, I'm guessing the denominator has to have a power > 1, which is why we have that condition on a. so it will fail the second time, i guess. but i can't formalize my argument (and I'm clueless about the third one).

sry :(
 
  • #4
any help please? :(
 

FAQ: Exploring Fourier Transforms and Integrability for Different Functions

What is a Fourier transform?

A Fourier transform is a mathematical tool used to decompose a function into its frequency components. It allows us to analyze and understand the different frequency components present in a signal.

How is a Fourier transform used in science?

Fourier transforms are used in a variety of scientific fields, including physics, engineering, and mathematics. They are particularly useful in signal processing, image processing, and data analysis to identify patterns and extract information from complex signals.

Can a Fourier transform be applied to any type of function?

Yes, a Fourier transform can be applied to any function that is continuous and has a well-defined Fourier integral. This means that most functions encountered in science can be transformed using Fourier analysis.

What is the difference between a Fourier transform and a Fourier series?

A Fourier transform is used for continuous signals, while a Fourier series is used for periodic signals. A Fourier series decomposes a function into a sum of sine and cosine functions, while a Fourier transform decomposes a function into its frequency components.

Are there any limitations to using Fourier transforms?

While Fourier transforms are a powerful tool, there are some limitations to their use. They can only be applied to functions that are continuous and have a finite Fourier integral. Additionally, they cannot capture information about the transient behavior of a signal, only its steady-state behavior.

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