Existance of Fourier transform

In summary, the sufficient condition for the existence of the Fourier transform of a function is absolute integrability. An example of such a function is f(t) = (1/π)(1/(1+t^2))|t|^(-1/2), as shown on page 177 of Fourier and Laplace Transforms by Beerends et al. The function is not square-integrable, meaning it has infinite energy and Parseval's Theorem will not hold for it. Attempts to find the Fourier transform using MATLAB's symbolic toolbox resulted in a very complex form. This experiment shows that there are functions whose Fourier transform exists, but do not have finite energy. The definition of Fourier transform used is X(jω) = ∫x
  • #1
kzhu
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Homework Statement


The sufficient condition of the existence of the Fourier transform of a function is that the function is absolutely integrable. I have identified a function that is absolutely integrable, but not square-integrable

[tex]f(t) = \frac{1}{\pi}\frac{1}{1+t^2}|t|^{\frac{-1}{2}}[/tex]

see page 177 of Fourier and Laplace Transforms by Beerends et al. What is the Fourier transform of this function? Could this be evaluated?

Homework Equations



Since this function is not square-integrable, does it mean it has infinite energy and the Parseval's Theorem will not hold for it?

The Attempt at a Solution


I attempted to use MATLAB symbolic toolbox to separately find the Fourier transform of the function
[tex]g(t) = \frac{1}{\pi}\frac{1}{1+t^2}[/tex]
and
[tex]h(t)=|t|^{\frac{-1}{2}}[/tex],

both of which exist but in a very complex form. I assume the Fourier transform of f(t) will be even more complex as Matlab failed to give an analytic form.

The implication of this little experiment shows that there are functions whose Fourier transform exists, but do not have finite energy.

Would appreciate if someone could confirm this with me.

Thank you.

kzhu
 
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  • #2
The definition of Fourier transform that I refer to is

[tex]X(j\omega) = \int_{-\infty}^{+\infty}x(t) e^{-j\omega t}dt[/tex]

and the inverse
[tex] x(t)=\frac{1}{2\pi} \int_{-\infty}^{+\infty} X(j\omega)e^{j\omega t} d\omega[/tex]

On a second thought, my question can read: Could someone provide a couple of functions that have Fourier transforms by these definition but do not have finite energy?

Thank you.

kzhu
 

FAQ: Existance of Fourier transform

What is the Fourier transform and why is it important?

The Fourier transform is a mathematical tool used in signal processing and analysis to decompose a signal into its frequency components. It is important because it allows us to understand the frequency content of a signal, which is crucial in many areas of science and engineering, such as image processing, audio signal processing, and data compression.

How does the Fourier transform work?

The Fourier transform works by representing a signal as a sum of sinusoidal functions with different frequencies, amplitudes, and phases. This transformation is done using an integral, which converts a time-domain signal into a frequency-domain signal.

What are the applications of the Fourier transform?

The Fourier transform has a wide range of applications in various fields, including signal processing, data analysis, image processing, and physics. It is used to analyze signals and filter out unwanted noise, compress data, and solve differential equations in physics and engineering.

Are there any limitations to the Fourier transform?

The Fourier transform has some limitations, such as assuming that the signal is periodic and infinite. It also cannot capture the instantaneous behavior of a signal, as it represents it in the frequency domain. Additionally, it may not be suitable for non-linear or non-stationary signals.

How does the Fourier transform relate to other mathematical concepts?

The Fourier transform is closely related to other mathematical concepts, such as the Laplace transform, which is used in solving differential equations. It is also related to complex numbers and the concept of frequency, which is a fundamental concept in physics and engineering. The Fourier transform is also used in conjunction with other transforms, such as the wavelet transform, for more complex signal analysis.

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