How can the Fourier series equation be used to represent the sawtooth function?

In summary, using the Fourier series equations, it can be shown that the given function represents the sawtooth function. The period of the function is T=2pi and the amplitude should not be divided by 2. The discrepancy between the given equation and the one on Wikipedia is due to a difference in the limits of integration.
  • #1
Winzer
598
0

Homework Statement


Prove:
[tex] f(t)=\sum_{i=1}^\infty (-1)^{n+1} \frac{Sin(n\omega t)}{n} [/tex]
represents the sawtooth function.

Homework Equations



Fourier Series Equations:
[tex] f(t)=\frac{a_0}{2}+\sum_{i=0}^\infty \left(a_n Cos(nt)+b_n Sin(nt) \right) [/tex]
where
[tex] a_n=\frac{2}{T}\int_{t}^{t+T} dt cos(nt) f(t) [/tex]
[tex] b_n=\frac{2}{T}\int_{t}^{t+T} dt sin(nt) f(t) [/tex]
[tex] a_0=\frac{2}{T}\int_{t}^{t+T} dt f(t) [/tex]

The Attempt at a Solution


I see from wikipedia:http://en.wikipedia.org/wiki/Fourier_series that they get
[tex] f(t)=2 \sum_{i=1}^\infty (-1)^{n+1} \frac{Sin(n\omega t)}{n} [/tex]
Is this 2 out in front because of their series is twice the period (T) of the one I'm given?

Anyways. The way I go about this is to first take out the [tex]a_n[/tex] since this is an odd function. The part I am stuck on is the limits of integration. The period is the time it takes to travel from the bottom of the sawtooth wave to the top of one right? So should T be (in the case of my given equation) [tex]-\frac{\pi}{2}[/tex] to [tex]\frac{\pi}{2}[/tex]?
 
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  • #2
Multiplying by two changes the amplitude of a function, not it's period. What's your definition of the sawtooth exactly?
 
  • #3
Dick said:
Multiplying by two changes the amplitude of a function, not it's period. What's your definition of the sawtooth exactly?
If you refer to the picture in the link that is saw tooth. My professor gave me a mathematica notebook with that exact picture; plotted with the equation I am suppose to prove. He graphed it with [tex]\omega=2\pi[/tex]. The amplitude appears greater then 1 though.
 
  • #4
So the amplitude just needs to be divided by 2?
I start off with:

[tex]
b_n=\frac{1}{T}\int_{t}^{t+T} dt sin(nt) f(t)
[/tex]

?
 
  • #5
Winzer said:
So the amplitude just needs to be divided by 2?
I start off with:

[tex]
b_n=\frac{1}{T}\int_{t}^{t+T} dt sin(nt) f(t)
[/tex]

?

No. The original formula you gave is correct, T=2pi. The 2 in the wikipedia comes from doing the integration. I don't think there is anything wrong with the definitions, you just aren't calculating something correctly.
 

1. What is a Fourier Series?

A Fourier Series is a mathematical representation of a periodic function using a combination of sinusoidal functions. It is used to approximate and analyze a wide range of functions in fields such as engineering, physics, and mathematics.

2. What is a Sawtooth Waveform?

A Sawtooth Waveform is a type of periodic function that has a linearly increasing or decreasing slope with sharp edges, resembling the shape of a sawtooth. It is commonly used in electronic circuits and audio signal generation.

3. How is a Sawtooth Waveform represented in a Fourier Series?

A Sawtooth Waveform can be represented in a Fourier Series by combining an infinite number of cosine waves with decreasing amplitudes and increasing frequencies. The resulting waveform will have a similar shape to a sawtooth, with the number of cosine waves determining the sharpness of the edges.

4. What are the applications of Fourier Series in relation to Sawtooth Waveforms?

Fourier Series has various applications in relation to Sawtooth Waveforms, including signal processing, filtering, and harmonic analysis. It is also used in the study of sound and vibrations, as well as in the design of electronic circuits and systems.

5. Are there any limitations to using Fourier Series to approximate Sawtooth Waveforms?

While Fourier Series can provide accurate approximations of Sawtooth Waveforms, it is not always possible to represent every function using this method. In some cases, the series may not converge, or the resulting waveform may not accurately represent the original function. Other methods, such as the Fast Fourier Transform, may be used to overcome these limitations.

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