Fourier transform of the sawtooth function

In summary, there is a difference between the two forms of the Fourier transform of the sawtooth function due to an error in the first method, where the wrong function was used. The correct form of the Fourier transform for the sawtooth function is obtained by first thinking of h(t) as the integral of a rectangular pulse g(t), and then using the Fourier property of integration in the time domain. This leads to a different result due to the inclusion of the Dirac delta function.
  • #1
jashua
43
0
Let the sawtooth function be defined as follows:

h(t) = t, 0<t<1,
h(t) = 0, elsewhere

The problem is two explain the reason for difference between the following two forms of the Fourier transform of h(t), which is denoted as H(f).

First method is straightforward, i.e., use the Fourier transform. Hence, we have:

H(f)= int (-inf to inf) t*exp(-j*2*pi*f*t) dt
H(f)= int (0 to 1) t*exp(-j*2*pi*f*t) dt

Then, using integration by part, we get (skipping some tedious steps)

H(f)= 1/(j*2*pi*f) * [sinc(f)*exp(-j*pi*f) - exp(-j*2*pi*f)].

On the other hand, if we think the sawtooth function h(t) as the integral of a rectangular pulse g(t), which is given as:

g(t)=1, 0<t<1,
g(t)=0, elsewhere,

such that h(t)=int (-inf to t) g(t) dt, then, using Fourier property (integration in the time domain), we get the following result:

H(f)=1/(j*2*pi*f) * sinc(f)*exp(-j*pi*f) + 1/2*dirac(f).

As you see these two results are different. Why?.. What is the mistake? Any help will be appreciated.
 
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  • #2
Hint: Is

[tex]\int_{-\infty}^2 g(t)\,dt[/tex]

equal to h(2)?
 
  • #3
Ops..! got it :)

So,

g(t) = rect(t-1/2) - dirac(t-1).

many thanks vela.
 
  • #4
jashua said:
Let the sawtooth function be defined as follows:

h(t) = t, 0<t<1,
h(t) = 0, elsewhere

The problem is two explain the reason for difference between the following two forms of the Fourier transform of h(t), which is denoted as H(f).

First method is straightforward, i.e., use the Fourier transform. Hence, we have:

H(f)= int (-inf to inf) t*exp(-j*2*pi*f*t) dt
H(f)= int (0 to 1) t*exp(-j*2*pi*f*t) dt

Then, using integration by part, we get (skipping some tedious steps)

H(f)= 1/(j*2*pi*f) * [sinc(f)*exp(-j*pi*f) - exp(-j*2*pi*f)].

On the other hand, if we think the sawtooth function h(t) as the integral of a rectangular pulse g(t), which is given as:

g(t)=1, 0<t<1,
g(t)=0, elsewhere,

such that h(t)=int (-inf to t) g(t) dt, then, using Fourier property (integration in the time domain), we get the following result:

H(f)=1/(j*2*pi*f) * sinc(f)*exp(-j*pi*f) + 1/2*dirac(f).

As you see these two results are different. Why?.. What is the mistake? Any help will be appreciated.

Your first H(f) = int (-inf to inf) t*exp(-j*2*pi*f*t) dt is not the F.T of the sawtooth function h(t); it is the F.T of the function k(t) = t for all t in R. Of course, your second form H(f)= int (0 to 1) t*exp(-j*2*pi*f*t) dt is correct for h(t).

RGV
 
  • #5
thank you very much for your correction in my question.
 

What is the Fourier transform of the sawtooth function?

The Fourier transform of the sawtooth function is a mathematical tool used to decompose a periodic signal into its constituent frequencies.

How is the Fourier transform of the sawtooth function calculated?

The Fourier transform of the sawtooth function can be calculated using the Fourier transform formula, which involves integrating the function over its period.

What are the properties of the Fourier transform of the sawtooth function?

The Fourier transform of the sawtooth function has an infinite number of discrete frequencies, with the amplitude of each frequency decreasing as the frequency increases. It is also an odd function, meaning that it is symmetric about the origin.

What is the significance of the Fourier transform of the sawtooth function in signal processing?

The Fourier transform of the sawtooth function is commonly used in signal processing to analyze and filter signals. It allows us to see the different frequencies present in a signal and can help us identify and remove noise.

Can the Fourier transform of the sawtooth function be applied to non-periodic signals?

No, the Fourier transform of the sawtooth function is only applicable to periodic signals. For non-periodic signals, other Fourier transforms such as the Fourier transform or the Laplace transform must be used.

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