Preserving Essential Features in Fourier Series Approximations

In summary: N might not be an accurate model.In summary, the process of transforming a function in Fourier series can discard information at high frequencies.
  • #1
neelakash
511
1
I hope that this is the appropriate forum to ask something about Fourier series.
My question is a little intuitive.Say I expand a function in Fourier series with
n=-∞ to n=∞.The graph of the function is available.

Now suppose,I cut off some terms for which |n|>N and expand the function.It will not be a Fourier series any more.But I am not worried about that.All I want to know whether this process is capable to preserve the essential feature of the graph.If terms like that (|n|>N) contribute very small to the actual series,then what I am telling is possible with a good approximation.Please let me know...

I encountered this problem in deriving the Parsevals formula in a Quantum Mechanics book where they have folowed the procedure in "approximation in the mean".
 
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  • #2
(deleted)
 
Last edited:
  • #3
It's possible that the terms on the ends of the series are insigificant and can be ignored, but this is not always the case. It depends upon the function that is being transformed.

In general, though, well-behaved functions do not contain significant energy out to infinite frequencies, and very high frequency information can thus be discarded.

- Warren
 
  • #4
Say your function [itex]f[/itex] is in [itex]C^k[/itex]. Let [itex]f_n[/itex] denote the n-th Fourier coefficient. Then one can prove that [itex]n^k f_n\rightarrow 0[/itex] as [itex]n\rightarrow \infty[/itex].
Is that enough for your problem?
 
  • #5
to nicktacik:
(deleted)
---means?

to chroot:
In general, though, well-behaved functions do not contain significant energy out to infinite frequencies, and very high frequency information can thus be discarded.
Say I am talking about a pulse like a Gaussian (momentum representation of wave function).Now take its F.T. which is also a Gaussian(wave function).Then I can assume what you say...right?

to cliowa,perhaps no.Because I am cutting an infinite limit integral into a summation with limit N.
 

1. What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as an infinite sum of sine and cosine waves. It is used to decompose a complex function into simpler components, making it easier to analyze and understand.

2. How is a Fourier series calculated?

A Fourier series is calculated by using a formula that involves integrating the function over one period and solving for the coefficients of the sine and cosine terms. These coefficients determine the amplitude and frequency of each component wave in the series.

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

A Fourier series is used for periodic functions, while a Fourier transform is used for non-periodic functions. Additionally, a Fourier transform produces a continuous spectrum of frequencies, while a Fourier series only includes discrete frequencies.

4. Why is understanding Fourier series important?

Fourier series are used in many fields, such as signal processing, engineering, and physics, to analyze and manipulate signals and data. Understanding Fourier series allows for a deeper understanding of these fields and their applications.

5. What are common sources of confusion when working with Fourier series?

Some common sources of confusion include understanding the concept of convergence, choosing the appropriate interval for the series, and understanding the relationship between a function and its Fourier series representation. It is important to have a solid understanding of the underlying principles and formulas to avoid confusion when working with Fourier series.

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