Fourier Series complex coefficients

In summary, the author finds the coefficient c_n by solving the equation c_n=\frac{1}{T}\int^T_0 f(t) e^{\frac{-i2\pi nt}{T}}dt. They use limits between 0 and T/2 to calculate it. Lastly, c_n is e^{-in\pi} for odd/even n.
  • #1
jellicorse
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I have been trying to follow how the complex Fourier coefficients are obtained; the reference I am using is at www.thefouriertransform.com. However I am unable to follow the author's working exactly and wondered if anyone could help me see where I am going wrong.

First, I understand that the coefficient [itex]c_n=\frac{1}{T}\int^T_0 f(t) e^{\frac{-i2\pi nt}{T}}dt[/itex]

Given a square wave, of period 2T, and amplitude :

http://s90.photobucket.com/user/jonnburton/media/SqareWave_zpsbdf193c1.jpg.html

It can be seen directly from the graph that [itex]c_0=\frac{1}{2}[/itex] (I also managed to calculate this, too.)

But I can't follow how the author obtained expressions for [itex]c_n[/itex].

This is what I have done in attempt to obtain [itex]c_n[/itex]:

[itex]c_n=\frac{1}{T}\int^{\frac{T}{2}}_0 1 \cdot e^{\frac{-i2\pi nt}{T}}dt[/itex]

[tex]\frac{1}{T}\left[\frac{T e^{\frac{-i2\pi nt}{T}}}{i2\pi n}\right]^{\frac{T}{2}}_0[/tex]

[tex]\frac{1}{T}\left[\left(\frac{T e^{-in\pi}}{in2\pi}\right)-\left(\frac{T}{in2\pi}\right)\right][/tex]

[tex]\left(\frac{e^{-in\pi}}{in2\pi}-\frac{1}{in2\pi}\right)[/tex]

However, the expression the author finds is:

[tex]\frac{1}{i\pi n}[/tex] for odd n, and zero for even n.
 
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  • #2
You seem to be missing a minus sign in your integral.

Also, simply for consistency, the limits you originally give (between 0 and T) aren't the limits you say you end up using (between 0 and T/2).

Lastly, what is [itex] e^{-in\pi} [/itex] for odd/even [itex] n [/itex]? Recall [itex] e^{in\pi} = cos(n\pi) + isin(n\pi) [/itex].
 
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  • #3
Thanks for the hints Silversonic. I will go back through it again but I think I can see how this works out now!

(I just changed the limits because I though it wasn't necessary to integrate beyond [itex]\frac{T}{2}[/itex] because the function there is zero.)
 
  • #4
jellicorse said:
(I just changed the limits because I though it wasn't necessary to integrate beyond [itex]\frac{T}{2}[/itex] because the function there is zero.)

Okay, the picture won't load for me. That could be an issue on my end.
 
  • #5
Not sure why it wasn't working; I've just typed the URL in again and I think it's OK now.
 

FAQ: Fourier Series complex coefficients

What is a Fourier series complex coefficient?

A Fourier series complex coefficient is a numerical value that represents the contribution of a specific sinusoidal function in a Fourier series. It is a complex number with a real and an imaginary component.

How are Fourier series complex coefficients calculated?

Fourier series complex coefficients can be calculated using the Fourier series formula, which involves integrating the periodic function being analyzed with respect to time and multiplying it by a complex exponential function. This process is repeated for each term in the series.

Can Fourier series complex coefficients be used for non-periodic functions?

No, Fourier series complex coefficients are only applicable for periodic functions. Non-periodic functions would require a different mathematical approach, such as the Fourier transform.

What is the significance of the magnitude and phase of Fourier series complex coefficients?

The magnitude of a Fourier series complex coefficient represents the amplitude of the corresponding sinusoidal function, while the phase represents the offset or shift from the original function. These values are important in analyzing the behavior of a periodic function and can help in reconstructing the original function from its Fourier series representation.

How are Fourier series complex coefficients used in practical applications?

Fourier series complex coefficients have a wide range of applications in various fields such as signal processing, image and sound compression, and solving differential equations. They are also used in analyzing the frequency spectrum of a periodic signal, which has numerous applications in engineering, physics, and mathematics.

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