Fourier Series - proving a sum

In summary: The first sum is -\sum_{n=1,nodd} \frac{4}{n^2 \pi} e^{inx}+\frac{\pi}{2} (even terms \hat{f}(n)=0), and the second sum is -\sum_{n=1}^{\infty} \frac{1}{(2n+1)^4} = \frac{\pi^4}{96}.
  • #1
ramdayal9
3
0

Homework Statement


Let [itex]f(x)=x[/itex] on [itex] [-\pi,\pi) [/itex] and peridically extended. Compute the Fourier series and hence show:

[itex] \sum_{n \geq 1,nodd} \frac{1}{n^2} = \frac{\pi^2}{8} [/itex] and [itex] \sum_{n \geq 1} \frac{1}{n^2} = \frac{\pi^2}{6} [/itex]

Homework Equations



Parseval's equality

The Attempt at a Solution


I computed the Fourier series to be [itex] -\sum_{n=1,nodd} \frac{4}{n^2 \pi} e^{inx}+\frac{\pi}{2} [/itex] (even terms [itex]\hat{f}(n)=0 [/itex]) and proved the first sum (letting x=0).
How would I compute the second part? how do i get the whole sum from this? I tried to slipt the sum into even and odd parts, but i don't know how to compute the even sum when I don't have any terms for the even sum! thanks
 
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  • #2
You can't. If, in fact, all terms with even indices are 0, then "[itex]\sum_{n\ge 1, n odd}[/itex]" and [itex]\sum_{n\ge 1}[/itex] must be the same!
 
  • #3
HallsofIvy said:
You can't. If, in fact, all terms with even indices are 0, then "[itex]\sum_{n\ge 1, n odd}[/itex]" and [itex]\sum_{n\ge 1}[/itex] must be the same!
Ok, so how would I use what I have to prove the second sum? That's assuming that Fourier series is right - I think it is, because the first sum works out. On a related note, how would I go about proving that [itex] \sum_{n=0}^{\infty} \frac{1}{(2n+1)^4} = \frac{\pi^4}{96}[/itex]? I have started by saying that this is equivalent to the sum [itex] \sum_{n \geq 1, n odd} \frac{1}{n^4} [/itex]. I use a similar method as before and consider the function [itex] f(x) = |x^3| [/itex] on [itex] [-\pi, \pi) [/itex] but I don't seem to get the sum I require in the end...I get the sum of even numbers instead!
Thanks
 
  • #4
ramdayal9 said:

Homework Statement


Let [itex]f(x)=x[/itex] on [itex] [-\pi,\pi) [/itex] and peridically extended. Compute the Fourier series and hence show:

[itex] \sum_{n \geq 1,nodd} \frac{1}{n^2} = \frac{\pi^2}{8} [/itex] and [itex] \sum_{n \geq 1} \frac{1}{n^2} = \frac{\pi^2}{6} [/itex]


Homework Equations



Parseval's equality

The Attempt at a Solution


I computed the Fourier series to be [itex] -\sum_{n=1,nodd} \frac{4}{n^2 \pi} e^{inx}+\frac{\pi}{2} [/itex] (even terms [itex]\hat{f}(n)=0 [/itex]) and proved the first sum (letting x=0).
How would I compute the second part? how do i get the whole sum from this? I tried to slipt the sum into even and odd parts, but i don't know how to compute the even sum when I don't have any terms for the even sum! thanks
I don't get the same Fourier series for f(x)=x that you do.
 

Related to Fourier Series - proving a sum

1. What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sine and cosine functions. It allows us to decompose a complex function into simpler components and analyze its behavior.

2. How do you prove a Fourier series sum?

To prove a Fourier series sum, you need to use the properties of orthogonality and completeness of sine and cosine functions. This involves evaluating the integral of the function multiplied by each sine and cosine term, and using the orthogonality property to simplify the expression.

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

A Fourier series is used to represent a periodic function, while a Fourier transform is used to represent a non-periodic function. A Fourier series is composed of discrete frequencies, while a Fourier transform is composed of continuous frequencies.

4. Can any function be represented by a Fourier series?

No, a function must satisfy certain conditions such as periodicity and square integrability to be represented by a Fourier series. Otherwise, the resulting series will not converge to the original function.

5. What is the practical application of Fourier series?

Fourier series have many practical applications in fields such as signal processing, image and sound compression, and solving differential equations. They are also used in physics and engineering to analyze the behavior of periodic systems.

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