Fourier series and orthogonality, completeness

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SUMMARY

The discussion centers on the concepts of completeness and orthogonality in Fourier series. It establishes that if a function f(x) is orthogonal to all basis functions ϕ_n, then the set of functions {ϕ_n} cannot be complete. The participants clarify that while Fourier series can yield values for periodic signals within the interval of -π to π, this does not imply completeness of the signal representation. Instead, it highlights the necessity of approximations when dealing with non-finite or partially known signals.

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  • Understanding of Fourier series and their properties
  • Knowledge of orthogonal functions and their significance
  • Familiarity with the concept of completeness in functional spaces
  • Basic principles of signal processing and periodic functions
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  • Study the implications of completeness in functional analysis
  • Learn about the properties of orthogonal systems in signal processing
  • Explore the differences between complete and incomplete Fourier series
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Mathematicians, signal processing engineers, and students studying Fourier analysis who seek to deepen their understanding of orthogonality and completeness in function spaces.

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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