Fourier series and orthogonality, completeness

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Discussion Overview

The discussion revolves around the concepts of Fourier series, orthogonality, and completeness within the context of mathematical analysis. Participants explore the implications of these concepts on the representation of functions and signals, particularly focusing on the conditions under which certain equations hold true.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions how an inequality arises from an assumption in the context of completeness and orthogonality, suggesting that if the system is complete and orthogonal, then the inner product should only yield zero when the function itself is zero.
  • Another participant emphasizes the necessity of completeness in an orthogonal system, indicating that the comment on page 10 refers to an arbitrary orthogonal system.
  • A participant seeks clarification on the implications of the inner product being zero for complete series, positing that if this holds, then Fourier series must also be zero, which contradicts the known values obtained for signals within a specified interval.
  • Discussion includes an example of an orthogonal system that is not complete, highlighting that using only cosines would prevent the representation of functions like sin(x).
  • There is a contention regarding the relationship between completeness and the inner product being zero, with one participant asserting that if the inner product is zero for all basis functions, then the set cannot be complete.
  • Participants discuss the implications of periodic signals and the conditions under which approximations may be necessary, particularly when signals are finite or not defined over the interval [-π, π].

Areas of Agreement / Disagreement

Participants express differing views on the implications of orthogonality and completeness, with no consensus reached regarding the conditions under which Fourier series yield non-zero values or the nature of approximations involved in signal representation.

Contextual Notes

Participants note limitations related to the completeness of the function sets being discussed, as well as the potential for approximations when dealing with finite or periodic signals. The discussion remains open-ended regarding the mathematical conditions and definitions involved.

kidsasd987
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http://ms.mcmaster.ca/courses/20102011/term4/math2zz3/Lecture1.pdfOn pg 10, the example says f(x)=/=0 while R.H.S is zero. It is an equations started from the assumption in pg 9; f(x)=c0f(x)0+c1f(x)1…, then how do we get inequality?

if the system is complete and orthogonal, then (f(x),ϕ_n(x))=0, which makes sense only when f(x)=0.
but we know for Fourier series, we get values for Rhs and Lhs.
 
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kidsasd987 said:
if the system is complete and orthogonal, then (f(x),ϕ_n(x))=0, which makes sense only when f(x)=0.
That's the key word. The comment on p. 10 is for an arbitrary orthogonal system. That is why completeness is necessary, as explained on p. 11.
 
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DrClaude said:
That's the key word. The comment on p. 10 is for an arbitrary orthogonal system. That is why completeness is necessary, as explained on p. 11.

Could you explain the details?

Also, if (f(x),ϕ_n(x))=0 holds in general for complete series, then Fourier series must be also zero since they are complete.
however we know that for signals we do get values within the interval of pi and -pi. is this because what we usually solve for signal input f(t) is not complete?

so we are approximating the signal?
 
kidsasd987 said:
Could you explain the details?
Look at p. 12, where an example is given of an orthogonal system that is not complete. Using only cosines, you could never write an expression for e.g. sin(x).

kidsasd987 said:
Also, if (f(x),ϕ_n(x))=0 holds in general for complete series, then Fourier series must be also zero since they are complete.
But it's the other way around. If ##(f, \phi_n) = 0## for a given ##f(x)## and for all ##\phi_n##, then ##\{\phi_n\}## is not a complete set.

kidsasd987 said:
however we know that for signals we do get values within the interval of pi and -pi. is this because what we usually solve for signal input f(t) is not complete?

so we are approximating the signal?
I'm not sure what you are asking here. If the signal is periodic but not on the interval ##[-\pi,\pi]##, then it is trivial to scale/shift it to that interval. If the signal is finite in time, then it is delt with the same way. If the signal is not finite, or only part of it is known, then indeed thre are approximations being made.
 

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