Generalisation of Parseval's Theorem via Convolution Theorem

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SUMMARY

This discussion focuses on the generalization of Parseval's Theorem through the application of the Convolution Theorem in the context of Fourier analysis. The participant explores the relationship between the Fourier coefficients of a function and its powers, specifically examining the case of the fourth power of a function. The conclusion drawn is that the manipulation of Fourier coefficients using convolution is valid, provided that convergence conditions are met, and clarifies that the discrete convolution is effectively the continuous convolution restricted to integers.

PREREQUISITES
  • Understanding of Fourier coefficients and Parseval's Theorem
  • Knowledge of convolution operations in Fourier analysis
  • Familiarity with L^{p}-norms and their properties
  • Basic concepts of integrable functions and periodicity
NEXT STEPS
  • Study the application of the Convolution Theorem in Fourier analysis
  • Explore the properties of L^{p}-norms in relation to Fourier coefficients
  • Investigate the convergence conditions for integrals in multi-dimensional spaces
  • Learn about discrete versus continuous convolution and their implications in analysis
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Mathematicians, students of Fourier analysis, and researchers working on integrable functions and their properties in the context of harmonic analysis.

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Homework Statement


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Suppose we have a 2\pi-periodic, integrable function f: \mathbb{R} \rightarrow \mathbb{C} whose Fourier coefficients are known. Parseval's theorem tells us that:

\sum_{n = -\infty}^{\infty}|\widehat{f(n)}|^2 = \frac{1}{2\pi}\int_{-\pi}^{\pi}|f(x)|^{2}dx,

where \widehat{f(n)} are the Fourier coefficients of f.

Suppose we instead want to replace f(x) with f(x)^{q}, say: then it would suffice to determine the Fourier coefficients of the q-th power of f. Is repeated application of the convolution theorem the usual way of finding powers of the Fourier coefficients of functions, where the Fourier coefficients of the original function are already known?

Homework Equations


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f \ast g denotes the convolution of f and g, given by (f \ast g)(t) := \int_{-\infty}^{\infty} f(\tau)g(t - \tau)d\tau, and \widehat{f \ast g} = \hat{f} \cdot \hat{g} is the convolution theorem for the Fourier transforms of f and g.

The Attempt at a Solution


Suppose that we are interested in \int_{-\pi}^{\pi}|f(x)|^{4} dx. I would like to know if it is valid to say the following:

\frac{1}{2\pi}\int_{-\pi}^{\pi}|f(x)|^{4}dx = \frac{1}{2\pi}\int_{-\pi}^{\pi}|(f(x))^{2}|^{2}dx = \sum_{n = -\infty}^{\infty} |\widehat{f(n)^{2}}|^{2} = \sum_{n = -\infty}^{\infty} | (\hat{f} \ast \hat{f})(n)|^{2}.

The reason I am interested in this is because I'm working on bounding a class of L^{p}-norms using the asymptotics of Fourier coefficients, and hoping to modify this slightly to integrate functions over a d-cube [0,2\pi)^d. This seems to be a complicated procedure however, since additional conditions need to be imposed on the functions to guarantee the convergence of the integral in \mathbb{R}^d.
 
Last edited:
Thanks for the automated response. I posted the same question on MathSE, and was told that the manipulation is correct as long as everything converges, although one should note that the convolution is on \mathbb{Z} rather than on \mathbb{R}. The only question I have left is whether that means I should be using the discrete convolution, or if I should still be using the continuous convolution restricted to \mathbb{Z} (if such a thing exists).

EDIT: I've just realized that the discrete convolution is precisely the continuous convolution restricted to the integers, so the question for this post has been answered. However, if anyone has any comments about the manipulation in post #1, I would greatly appreciate hearing them.
 
Last edited:

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