Fourier transform same as signal.

In summary, the conversation discusses a search for signals that have themselves as their Fourier transform, with two examples provided. The speaker also asks for suggestions of other signals with this property.
  • #1
bhupala
6
0
Hi friends,

I was looking for signals which will have themselves as the Fourier transform. Few of them are given below.

[tex]
\frac{1}{\sqrt{2\pi}}e^{-\frac{t^2}{2}}\longrightarrow e^{-\frac{\omega^2}{2}}
[/tex]

[tex]
\sum_{k=-\infty}^{\infty}\delta(t-kT)\longrightarrow \frac{2\pi}{T}\sum_{n=-\infty}^{\infty}\delta(\omega-\frac{2\pi n}{T})
[/tex]

can you suggest any other signals which satisfy the property?

regards,
bhupala.
 
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  • #2
A pulse in the shape of a gaussian curve?
 
  • #3
That is what I have given as the first example.
 
  • #4
bhupala said:
Hi friends,

I was looking for signals which will have themselves as the Fourier transform.
.
.
.
... can you suggest any other signals which satisfy the property?

regards,
bhupala.
Interesting question. What is your application?
 

What is a Fourier transform?

A Fourier transform is a mathematical tool that converts a signal from its original domain (such as time or space) to a representation in the frequency domain. This allows us to see the different frequencies present in a signal and their respective strengths.

How is a Fourier transform related to signals?

A Fourier transform is used to analyze signals, which are patterns of data over time or space. By converting a signal to the frequency domain, we can better understand its behavior and characteristics, such as its frequency components and energy distribution.

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

A Fourier transform is a continuous function that converts a signal from its original domain to the frequency domain, whereas a Fourier series is a discrete function that decomposes a signal into a sum of sinusoidal functions. A Fourier transform is typically used for continuous signals, while a Fourier series is used for periodic signals.

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

Yes, a Fourier transform can be applied to any type of signal, as long as the signal is defined over a continuous domain. However, in some cases, the signal may need to be modified or preprocessed before applying the transform, such as when dealing with non-stationary signals or signals with discontinuities.

What are some practical applications of Fourier transform?

Fourier transform has a wide range of applications in various fields, including signal processing, image and audio compression, data analysis, and physics. It is also used in technologies such as MRI imaging, radio astronomy, and speech recognition.

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