Problem with the sum of a Fourier series

In summary, the Fourier sum in the region ##x=2+\epsilon\ ## bounces between ##\log 3 ## and ##\log 2 ##.
  • #1
Amaelle
310
54
Homework Statement
Look at the image
Relevant Equations
Fourier serie
Good day
1612882634390.png


I really don't understand how they got this result? for me the sum of the Fourier serie of of f is equal to f(2)=log(3)
any help would be highly appreciated!
thanks in advance!
 
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  • #2
Hi,
Sounds reasonable. However:
what is the sum at ##\ x=2+\epsilon\ ## with ##\ \ 0<\epsilon <<< 1\ ## ?
 
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  • #3
thanks for your prompt answer,
as I saw it, I can't plug it the function f(x), so I really have no clue ...:oldconfused:
 
  • #4
The function is periodic, so ##f(2+\epsilon) = f(-{1\over2}+\epsilon)##.
What is ## f(-{1\over2})## ?
 
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  • #5
f(-1/2)=f(2)=log(3) as they are periodic, right?
 
  • #6
And it jumps down to what when you go a little further ?
 
  • #7
so maybe I got you
In this region the value of f(-1/2)=0 so the we are in discountinous stepwise function, in which tthe value of f(2+e)
bounces between 2 and 0?
 
  • #8
i mean jump between log3 and 0
 
  • #9
## f(-{1\over2}) = 0 ## ? :nb)
 
  • #10
[tex]\lim_{\epsilon \to 0}f(-\tfrac12 + \epsilon) = \lim_{\epsilon \to 0} |\log(-\tfrac12 + \epsilon)| = \lim_{\epsilon \to 0}\log(\tfrac{2}{1 - 2\epsilon}) = ?[/tex]
 
  • #11
BvU said:
## f(-{1\over2}) = 0 ## ? :nb)
no I meant f(-1/2 +ε) =log(1+ε) =0 because -1/2 does not belong to the definition domain
 
  • #12
pasmith said:
[tex]\lim_{\epsilon \to 0}f(-\tfrac12 + \epsilon) = \lim_{\epsilon \to 0} |\log(-\tfrac12 + \epsilon)| = \lim_{\epsilon \to 0}\log(\tfrac{2}{1 - 2\epsilon}) = ?[/tex]
log(2)
 
  • #13
Amaelle said:
log(2)
but sorry just one question
lim f(-1/2 + epsilon)= lim |log(-1/2+epsilon)|=lim -log(-1/2+ epsilon)=lim log(2/(2epsilon-1)) I think there us a small problem with the sign no?
 
  • #14
What is ##\bigl |\log {1\over 2} \bigr |## ?
 
  • #15
Amaelle said:
because -1/2 does not belong to the definition domain
Correct, but does it make any difference for the Fourier series ? Do you calculate something different for ##\ (-{1\over 2}, 2]\ ## than for ##\ [-{1\over 2}, 2)\ ## ?
 
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  • #16
BvU said:
Correct, but does it make any difference for the Fourier series ? Do you calculate something different for ##\ (-{1\over 2}, 2]\ ## than for ##\ [-{1\over 2}, 2)\ ## ?
not does not
 
  • #17
BvU said:
What is ##\bigl |\log {1\over 2} \bigr |## ?
|log(2)|=log(2)
 
  • #18
Yes; I hope you got it right: ##\ \bigl |\log{1\over 2}\bigr | = |-\log 2\bigr | = \log 2 \ .##

So at ##x=2## the Fourier sum jumps from ##\log 3 ## to ##\log 2 ##. What's the average ?

##\ ##
 
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  • #19
log(6)/2, thanks a million!
 
  • #20
So somehow the subtle difference between ranges ##\ (-{1\over 2}, 2]\ ## and ##\ [-{1\over 2}, 2)\ ## is 'lost in transformation' :rolleyes:

##\ ##
 
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  • #21
BvU said:
So somehow the subtle difference between ranges ##\ (-{1\over 2}, 2]\ ## and ##\ [-{1\over 2}, 2)\ ## is 'lost in transformation' :rolleyes:

##\ ##
yes , thanks a million, that was a nice explanation!
 

FAQ: Problem with the sum of a Fourier series

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 is used to approximate complex functions and is commonly used in signal processing and image analysis.

What is the problem with the sum of a Fourier series?

The problem with the sum of a Fourier series is that it may not converge to the original function. This is known as the Gibbs phenomenon and results in overshoots and oscillations near discontinuities in the function.

How can the problem with the sum of a Fourier series be minimized?

The problem with the sum of a Fourier series can be minimized by using a larger number of terms in the series. Additionally, using a different type of series, such as a Chebyshev series, can also help reduce the error.

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

A Fourier series is used to approximate a periodic function, while a Fourier transform is used to decompose a non-periodic function into its frequency components. The Fourier transform is a continuous function, while the Fourier series is a discrete function.

Are there any real-world applications of Fourier series?

Yes, Fourier series have numerous real-world applications, including signal processing, image analysis, and data compression. They are also used in fields such as physics, engineering, and economics to model and analyze complex systems.

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