How Does the Fourier Series of a Square Wave Lead to the Leibniz Formula for Pi?

In summary, the conversation is discussing finding the alternating sum that equals pi from the Fourier series of a square wave at x=pi/2. The square wave is defined as 1 at x=pi/2 and the process of evaluating the Fourier series at this point is explained. However, the resulting equation is not correct and the conversation ends with the realization that there may have been a mistake in the calculations.
  • #1
FrogPad
810
0
Here is the question:
At [itex] x= \frac{\pi}{2} [/itex] the square wave equals 1. From the Fourier series at this point find the alternating sum that equals [itex] \pi [/itex].
[tex] \pi = 4(1 - \frac{1}{3}+\frac{1}{5}-\frac{1}{7} + \ldots [/tex]

I do not understand what the question is asking. I'm not knowledgeable enough with Fourier series to understand it I believe. This is my best guess:

I need to find the Fourier series of the square wave starting at [itex] \frac{\pi}{2} [/itex] fand this will "magically" yield the alternating series for [itex] \pi [/itex].

But I don't understand what "the square wave equals 1" part means. Do I define the square wave to jump to 1 at [itex] \frac{pi}{2} [/itex] instead of the typical wave (typical for me) where the wave is -1 from -pi to 0, and jumps to 1 at 0 to pi ?

Any help clarifying would be swell. Thanks :)

What's up with the LaTeX by the way?
 
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  • #2
FrogPad said:
Here is the question:
At [itex] x= \frac{\pi}{2} [/itex] the square wave equals 1. From the Fourier series at this point find the alternating sum that equals [itex] \pi [/itex].
[tex] \pi = 4(1 - \frac{1}{3}+\frac{1}{5}-\frac{1}{7} + \ldots [/tex]

It says consider a square wave that is 1 at pi/2. The most casual one would be the one you mention later: the wave is -1 from -pi to 0, and jumps to 1 at 0 to pi. The Fourier series of a function at a point, if it converges towards the function, equals the function evaluated at that point. See what you get when you evaluate the Fourier series of the square wave at x=pi/2.
 
  • #3
For a problem before this one, I just got done evaluating the Fourier series for a square wave with properties:

-1 , -pi to 0
1 , 0 to pi

[tex] \hat f(x) = \frac{4}{\pi}\left(\frac{\sin x}{1}+\frac{\sin 3x}{3}+\frac{\sin 5x}{5}+\ldots\right) [/tex]

Evaluating the Fourier series at [itex] \frac{\pi}{2} [/itex] yields:
(It took me so long to realize what this means. :)

[tex] \hat f(\frac{\pi}{2}) = \frac{4}{\pi}\left(\frac{\sin \frac{\pi}{2}}{1}+\frac{\sin \frac{\pi}{2}}{3}+\frac{\sin \frac{\pi}{2}}{5}+\ldots \right) [/tex]

[tex] \hat f(\frac{\pi}{2}) = \frac{4}{\pi}\left(1 + \frac{1}{3} + \frac{1}{5} + \ldots \right)[/tex]

We know that the square wave at pi/2 is equal to 1 so:
[tex] 1 = \frac{4}{\pi}\left(1 + \frac{1}{3} + \frac{1}{5} + \ldots \right) [/tex]

This can then be solved for [itex] \pi [/itex]. But! This is not correct. So is my Fourier series for the square wave wrong?
 
  • #4
FrogPad said:
[tex] \hat f(x) = \frac{4}{\pi}\left(\frac{\sin x}{1}+\frac{\sin 3x}{3}+\frac{\sin 5x}{5}+\ldots\right) [/tex]

Evaluating the Fourier series at [itex] \frac{\pi}{2} [/itex] yields:
(It took me so long to realize what this means. :)

[tex] \hat f(\frac{\pi}{2}) = \frac{4}{\pi}\left(\frac{\sin \frac{\pi}{2}}{1}+\frac{\sin \frac{\pi}{2}}{3}+\frac{\sin \frac{\pi}{2}}{5}+\ldots \right) [/tex]

sin(3*pi/2) is not sin(pi/2)!
 
  • #5
hahahahah...
yeah, you are right !

man, I took this stupid cold medicine. I'm just going to go to bed and work on this in the morning, because obviously I'm making some really dumb mistakes!


thanks you guys :)
that was actually an interesting problem.
 

FAQ: How Does the Fourier Series of a Square Wave Lead to the Leibniz Formula for Pi?

What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sinusoidal functions. It allows for the decomposition of a complex function into simpler components, making it useful for analyzing and understanding periodic phenomena.

What is the purpose of a Fourier series?

The main purpose of a Fourier series is to approximate a periodic function using a finite number of terms. This can be useful in signal processing, image and sound compression, and many other applications where complex functions need to be simplified and analyzed.

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

A Fourier series represents a periodic function as a sum of sinusoidal functions with different frequencies and amplitudes, while a Fourier transform represents a non-periodic function as a sum of sinusoidal functions with different frequencies and complex amplitudes. In other words, a Fourier series is used for periodic functions, while a Fourier transform is used for non-periodic functions.

What is the relationship between Fourier series and frequency domain analysis?

Fourier series is a mathematical tool that allows us to analyze periodic functions in the frequency domain. It helps us understand the different frequency components present in a periodic function and their respective amplitudes. By converting a function from the time domain to the frequency domain, we can gain insights into its behavior and make predictions about its future behavior.

What are some real-world applications of Fourier series?

Fourier series has a wide range of applications in various fields, including physics, engineering, signal processing, and mathematics. Some examples of its real-world applications include analyzing sound and music, image processing, data compression, solving differential equations, and understanding the behavior of physical systems.

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