Using Cauchy Schwartz Inequality (for Integrals)

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SUMMARY

The discussion focuses on applying the Cauchy-Schwartz Inequality to integrals, specifically to demonstrate that \(\int_{a}^{b} |f(t)| dt \leq K^{2}(\log(b) - \log(a))\) given the condition \(\int_{-\infty}^{\infty} t |f(t)| dt < K\). The participants utilize the Cauchy-Schwartz Inequality in \(L^{2}\) space, setting \(h(t) = \sqrt{t}|f(t)|\) and \(g(t) = \frac{1}{\sqrt{t}}\). The conclusion reached is that while \(\int_{a}^{b} \frac{1}{t} dt\) simplifies to \(\log(b) - \log(a)\), proving \(\int_{a}^{b} t |f(t)|^{2} dt \leq K^{2}\) remains unresolved due to the limits not aligning.

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  • Familiarity with function behavior (even and odd functions)
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Homework Statement



Suppose [itex]\int_{-\infty}^{\infty}t|f(t)|dt < K[/itex]

Using Cauchy-Schwartz Inequality, show that [itex]\int_{a}^{b} \leq K^{2}(log(b)-log(a))[/itex]

Homework Equations



Cauchy Schwartz: [itex]|(a,b)| \leq ||a|| \cdot ||b||[/itex]

The Attempt at a Solution



Taking CS on [itex]L^{2}[/itex] gives us

[itex](|\int_{a}^{b}h(t)g(t)dt|)^{2} \leq (\int_{a}^{b}|h(t)|^{2}dt)(\int_{a}^{b}|g(t)|^{2}dt)[/itex]

Setting [itex]h(t)=\sqrt{t}|f(t)|[/itex] and [itex]g(t)=\frac{1}{\sqrt{t}}[/itex] we get

[itex](\int_{a}^{b}|f(t)|dt)^{2} \leq (\int_{a}^{b}t|f(t)|^{2}dt)(\int_{a}^{b}\frac{1}{t}dt)[/itex]

Obviously [itex]\int_{a}^{b}\frac{1}{t}dt[/itex] is [itex]log(b)-log(a)[/itex]

So we just need to show [itex]\int_{a}^{b}t|f(t)|^{2}dt \leq K^2[/itex]

Obviously this is true if [itex]\int_{a}^{b}t|f(t)|^{2}dt \leq (\int_{-\infty}^{\infty}t|f(t)|dt)^2[/itex]

But this is where I get stuck. The limits aren't equal for these two and the Cauchy Schwartz inequality is the wrong way around for them to work.
 
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your problem statement is probably wrong, since if f(x) is even or odd, K can obviously approach 0, the inequality you want to prove need not hold in general.
 

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