Fourier transform of Logarithm ?

In summary: The limit as x approaches negative infinity can be evaluated using Euler's Identity as sin(x) and cos(x) will always evaluate to zero as x approaches infinity.
  • #1
zetafunction
391
0
does anyone know how to calculate (in the sense of distribution) the Fourier transform of

[tex] f(x)= ln|x| [/tex]

that is to obtain the integral [tex] \int_{-\infty}^{\infty} dx ln|x|exp(iux) [/tex]
 
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  • #2
I guess the absolute value is the problem?

[tex]
\ln|x| = \begin{cases} \ln ( x), & \mbox{if } x \ge 0 \\ \ln (-x), & \mbox{if } x < 0. \end{cases}
[/tex]

Now you can split up the integral in a part that goes from -infinity to 0 and from 0 to infinity.
 
  • #3
Do I remember the definition of a distribution sense Fourier transform correctly, when I think that you want to learn something about the mapping

[tex]
s\mapsto \int\limits_{-\infty}^{\infty}\Big(\int\limits_{-\infty}^{\infty} s(x)e^{iux} dx\Big) \log|u| du,
[/tex]

where [itex]s:\mathbb{R}\to\mathbb{R}[/itex] is a Schwartz test function?

Looks pretty difficult task to me. Do you have some reason to believe that there exists something that could be done with these integrals?

update:

The expression I wrote is precisely the same thing as this:

[tex]
\lim_{R\to\infty} \int\limits_{-\infty}^{\infty} s(x) \Big(\int\limits_{-R}^R \log|u| e^{iux} du\Big) dx
[/tex]

So it could be that the definition using Schwartz test function looks like unnecessarily complicated. It's really only about the old fashioned "integrate first, take limit last"-stuff. In this case it could be the best to only to estimate the integral

[tex]
\int\limits_{-R}^R \log|u| e^{iux} du
[/tex]

and try to solve some relevant behavior in the limit [itex]R\to\infty[/itex].
 
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  • #4
Wolfram Integrator told that some integral function of [itex]\log(x)e^{Ax}[/itex] would be

[tex]
\frac{1}{A}\log(x)e^{Ax} - \frac{1}{A}\textrm{Ei}(Ax),
[/tex]

where Ei is the exponential integral. (Wolfram, Wikipedia)

It could be, that the problem can be solved by using some known asymptotic properties of the exponential integral.
 
Last edited:
  • #5
I think you can try to solve it using complex analysis. Consider the complex plan with z = x+iy. Now the integral can be solved in the complex domain, uisng Residue Theorem. Hope this helps.
 
  • #6
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  • #7
Thanks for the new method. It does solve most of the problem as the Fourier transform of 1/x was available in the table(entry 309). I had one problem, though. I am stuck at evaluating the limit for the expression exp(-i[tex]\omega[/tex]x)/x at the limits x approaching negative infinity. Can I use the Euler's identity and reason that as the sin and cos terms are always between -1 and 1, then as x approaches infinity on any side, it will always evaluate to zero. So, is the correct answer pi*w*sqn(w)
 
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  • #8
Jivesh said:
Thanks for the new method. It does solve most of the problem as the Fourier transform of 1/x was available in the table(entry 309). I had one problem, though. I am stuck at evaluating the limit for the expression exp(-i[tex]\omega[/tex]x)/x at the limits x approaching negative infinity. Can I use the Euler's identity and reason that as the sin and cos terms are always between -1 and 1, then as x approaches infinity on any side, it will always evaluate to zero. So, is the correct answer pi*w*sqn(w)

Show the magnitude goes to zero. The magnitude of the numerator is one.
 
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1. What is the Fourier transform of logarithm?

The Fourier transform of logarithm is a mathematical operation that converts a function in the time or spatial domain to its equivalent representation in the frequency domain. It is defined as the integral of the function multiplied by a complex exponential function.

2. How is the Fourier transform of logarithm calculated?

The Fourier transform of logarithm can be calculated using the formula: F(ω) = ∫-∞ f(t) e-iωt dt, where ω is the frequency variable, f(t) is the function in the time domain, and i is the imaginary unit. This integral can be solved using techniques such as integration by parts or the Fourier transform tables.

3. What is the significance of the Fourier transform of logarithm?

The Fourier transform of logarithm is an important tool in signal processing and data analysis. It allows us to analyze a signal or function in terms of its frequency components, which can provide insights into its behavior and characteristics. It is also used in various fields such as engineering, physics, and mathematics.

4. Can the Fourier transform of logarithm be inverted?

Yes, the Fourier transform of logarithm can be inverted using the inverse Fourier transform formula: f(t) = ∫-∞ F(ω) eiωt dω. This allows us to convert a function in the frequency domain back to its representation in the time domain.

5. Are there any applications of the Fourier transform of logarithm?

Yes, the Fourier transform of logarithm has various applications in fields such as digital signal processing, image processing, and data compression. It is also used in solving differential equations, calculating convolutions, and analyzing the frequency spectrum of a signal or function.

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