Regarding approximation theorem

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SUMMARY

The discussion centers on the approximation theorem, specifically the relationship between the effect of a periodic function f, defined as P(f) = 1/(2π) ∫_{-π}^π |f(t)|² dt, and Parseval's Theorem, which states P(f) = ∑_{n=-∞}^∞ |c_n|². Participants clarify that the N'th partial sum, P(Sn) = ∑_{n=-N}^N |c_n|², can be derived from the definition of effect. They conclude that the inequality P(Sn)/P(f) ≥ δ holds true only if ∑_{|n|>N} |c_n|² ≤ (1-δ)P(f).

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Hello,
The effect of a 2pi periodic function f is defined as
[tex]P(f) = 1/(2\pi) \int_{-\pi}^\pi |f(t)|^2 \ dt[/tex]
and Parsevals Theorem tells us that
[tex]P(f) = \sum_{n=\infty}^\infty |c_n|^2[/tex]. Now, it seems rather intuituve that the effect of the N'te partial sum is
[tex]P(Sn) = \sum_{n=-N}^N |c_n|^2[/tex] But what is the in-between math argument? And furthermore, how can i proove that the inequality [itex]P(Sn)/P(f) \geq \delta[/itex] is satisfied only if
[tex]\sum_{|n|>N} |c_n|^2 \leq (1-\delta)P(f)[/tex]

Thanks
 
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First Part:
You can define "partial sum" (almost) any way you want here. If you have a series
[tex] \sum_{n = A}^B \text{ (something)} \, ,[/tex]
any of the following are partial sums:
[tex] \begin{align*}<br /> f(S_1) &= \sum_{n = A^\prime}^B \text{ (something)} \, , \quad (A^\prime > A) \, ;\\ <br /> f(S_2) &= \sum_{n = A}^{B^\prime} \text{ (something)} \, , \quad (B^\prime < B) \, ;\\<br /> f(S_\text{crazy}) &= \sum_{n = -1249742}^{197494614} \text{ (something)} \, .\\<br /> \end{align*}[/tex]
(The limits in the last expression are both between A and B.)
You have it right. All you've done is written down a nice, symmetric partial sum, which is the one that will solve the...
Second Part:
Notice
[tex] P(f) = P(Sn) + \sum_{|n| > N} |c_n|^2 \, .[/tex]
Take it from there.
 
Last edited:
bigplanet401 said:
First Part:
You can define "partial sum" (almost) any way you want here. If you have a series
[tex] \sum_{n = A}^B \text{ (something)} \, ,[/tex]
any of the following are partial sums:
[tex] \begin{align*}<br /> f(S_1) &= \sum_{n = A^\prime}^B \text{ (something)} \, , \quad (A^\prime > A) \, ;\\ <br /> f(S_2) &= \sum_{n = A}^{B^\prime} \text{ (something)} \, , \quad (B^\prime < B) \, ;\\<br /> f(S_\text{crazy}) &= \sum_{n = -1249742}^{197494614} \text{ (something)} \, .\\<br /> \end{align*}[/tex]
(The limits in the last expression are both between A and B.)
You have it right. All you've done is written down a nice, symmetric partial sum, which is the one that will solve the...
Sorry, but I am not sure i understand what you're trying to say. Shouldn one use the definition of effect to show that
[tex]P(Sn) = \sum_{n=-N}^N |c_n|^2[/tex]
bigplanet401 said:
Second Part:
Notice
[tex] P(f) = P(Sn) + \sum_{|n| > N} |c_n|^2 \, .[/tex]
Take it from there.
Yes. Ok. I see, that greatest value of [tex]\sum_{|n| > N} |c_n|^2[/tex] is bound to be no higher than P(f), and only when [itex]\delta = 0[/itex]. And ofcourse when [itex]\delta = 1[/itex], [tex]\sum_{|n| > N} |c_n|^2 \leq 0[/tex]. But i can't see why all the in-between values of delta must satisfy
[tex]\sum_{|n| > N} |c_n|^2 \leq (1-\delta ) P(f)[/tex]
 

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