A concise "proof" of the Riemann-Lebesgue lemma

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SUMMARY

The Riemann-Lebesgue lemma can be proved by demonstrating that the Fourier transform of step functions converges to zero as the frequency approaches infinity. Step functions are dense in the space of integrable functions, specifically in ##L^1(\mathbb R,\mathcal B(\mathbb R),\lambda)##. The proof involves showing that the supremum of the difference between the Fourier transforms of a function and its approximating step function converges to zero, leveraging properties of convergence in ##L^\infty##. The triangle inequality is crucial in finalizing the proof, establishing that for sufficiently large ##n##, the Fourier transform of the original function approaches zero.

PREREQUISITES
  • Understanding of the Riemann-Lebesgue lemma
  • Familiarity with Fourier transforms
  • Knowledge of step functions and their properties
  • Concepts of convergence in ##L^1## and ##L^\infty## spaces
NEXT STEPS
  • Study the properties of Fourier transforms in detail
  • Explore the concept of dense subsets in functional analysis
  • Learn about convergence types in functional spaces
  • Investigate the implications of the Riemann-Lebesgue lemma in signal processing
USEFUL FOR

Mathematicians, particularly those specializing in functional analysis, signal processing engineers, and students studying advanced calculus or real analysis will benefit from this discussion.

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Roughly, at least in the text I'm currently reading, the Riemann-Lebesgue lemma states that the Fourier transform ##\hat f## of an ##L^1(\mathbb R,\mathcal B(\mathbb R),\lambda)## function ##f## vanishes at infinity. I have trouble understanding a concise proof of this lemma.
In the Riemann-Lebesgue lemma, the author says it suffices to prove $$\hat{f}(\xi)\underset{|\xi|\to\infty}{\to}0$$for step functions on ##\mathbb R## only (step functions are simple functions where the sets of the indicator functions are intervals in ##\mathbb R##). This is because the step functions are dense in ##L^1(\mathbb R,\mathcal B(\mathbb R),\lambda)## and so let ##(\varphi_n)## be a sequence of step functions that approximate ##f## in the ##L^1## norm, i.e. ##\|f-\varphi_n\|_1\to0## as ##n\to\infty##. Then we just have to observe \begin{align*}\sup_{\xi\in\mathbb R}|\hat{f}(\xi)-\hat{\varphi}_n(\xi)|&=\sup_{\xi\in\mathbb R}\left|\int f(x)e^{\mathrm{i}x\xi}\,\mathrm{d}x-\int \varphi_n(x)e^{\mathrm{i}x\xi}\,\mathrm{d}x\right|\\ &\leq\|f-\varphi_n\|_1\end{align*}

That's basically the end of the "proof". The above inequality shows ##\hat\varphi_n\to\hat f## in ##L^\infty## (since almost uniform convergence is equivalent to convergence in ##L^\infty##), but how does the proof of the lemma proceed (assuming we've shown the lemma holds for step functions)?
 
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I think I get it now (and it wasn't so hard, just use the triangle inequality :smile: ). $$|\hat f(\xi)|\leq |\hat{f}(\xi)-\hat{\varphi}_n(\xi)|+|\hat{\varphi}_n(\xi)|\leq\|\hat{f}-\hat{\varphi}_n\|_\infty+|\hat{\varphi}_n(\xi)|.$$Now pick ##n## so large that ##\|\hat{f}-\hat{\varphi}_n\|_\infty<\epsilon## and then for those ##n##, let ##|\xi|\to \infty##.
 

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