Dirac delta and fourier transform

In summary, the Dirac delta function and the complex exponential with frequency u are a Fourier transform pair. The equation given is not mathematically rigorous, but it can be understood in terms of the Fourier transform operator and distributions.
  • #1
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In my book the dirac delta is described by the equation on the attached picture. This realtion is derived from the Fourier transform, but I'm not sure that I understand what it says. If u=t it is clear that one gets f(u) in the Fourier inversion theorem. But why wouldn't u=t? In the derivation of the Fourier transform from the discrete Fourier series t was just changed to u in the expression of the coefficients to avoid confusion.
Can anyone try to picture what this expression fundamentally says? I should suspect that it is like the analogue of the ortogonality relation of the discrete Fourier series, but I can't quite understand it.
And what would the situation u≠t represent?
 

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  • #2
What it is saying is that

[tex]\delta(t - u)[/tex]
and
[tex]\exp(-iu\omega)[/tex]

are a Fourier transform pair. A complex exponential with "frequency" equal to [itex]u[/itex] has a Fourier transform with all of its energy concentrated at [itex]u[/itex].
 
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  • #3
P.S. The equation

[tex]\delta(t - u) = \frac{1}{2\pi}\int_{-\infty}^{\infty} \exp(i \omega(t-u) d\omega[/tex]

is mathematically nonrigorous. The integral on the right hand side does not actually exist for any values of [itex]u[/itex] and [itex]t[/itex]. What is true is that if [itex]\mathcal{F}[/itex] denotes the Fourier transform operator, then

[tex]\mathcal{F}(\delta(t-u)) = \exp(-i\omega u)[/tex]
and
[tex]\delta(t-u) = \mathcal{F}^{-1}(\exp(-i\omega u))[/tex]

in the sense of distributions. See here for more details:

http://en.wikipedia.org/wiki/Distribution_(mathematics)
 
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1. What is the Dirac delta function?

The Dirac delta function, denoted as δ(t), is a mathematical function that is used to represent a point mass or spike at a specific point in time. It is defined as zero for all values of t except at t=0, where it is infinite. The area under the curve of the Dirac delta function is equal to 1.

2. What is the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It transforms a function from the time domain to the frequency domain, where the amplitude of each frequency component can be visualized. It is commonly used in signal processing and image processing applications.

3. How are the Dirac delta function and Fourier transform related?

The Dirac delta function is the Fourier transform of a constant function. This means that a constant function can be expressed as an infinite sum of Dirac delta functions, with different magnitudes and shifted positions. The Fourier transform of a function can also be used to find the value of the function at any point in time.

4. What is the significance of the Dirac delta function and Fourier transform in science and engineering?

The Dirac delta function and Fourier transform have many applications in science and engineering, particularly in areas such as signal processing, image processing, and quantum mechanics. They are used to analyze and manipulate signals and images, as well as to solve differential equations and other mathematical problems.

5. Are there any limitations to using the Dirac delta function and Fourier transform?

One limitation of the Dirac delta function is that it is not a true function, as it is not defined at t=0. It is also considered an idealization and does not exist physically. The Fourier transform also has limitations, such as the requirement of functions to be integrable and the fact that it cannot be applied to all types of functions, such as functions with infinite discontinuities.

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