On commutativity of convolution

Click For Summary
SUMMARY

The discussion centers on the commutativity of convolution for real measurable functions on the measure space $(\mathbb R^d, \mathcal B(\mathbb R^d), \lambda)$, where $\lambda$ is the Lebesgue measure. It is established that for two functions $f$ and $g$, the convolution $f \ast g(x) = \int_{\mathbb R^d} f(x-y)g(y) \, \mathrm{d}y$ is well-defined under the condition that $\int_{\mathbb R^d} |f(x-y)g(y)| \, \mathrm{d}y < \infty$. The discussion confirms that $g \ast f(x) = f \ast g(x)$ due to the invariance of Lebesgue measure under translations and the symmetry $y \to -y$. The change of variables in the integration process is also clarified, emphasizing the importance of orientation in the integration limits.

PREREQUISITES
  • Understanding of Lebesgue measure and its properties
  • Familiarity with convolution operations in functional analysis
  • Knowledge of change of variables in multiple integrals
  • Basic concepts of measure theory and integration
NEXT STEPS
  • Study the properties of Lebesgue measure, particularly its invariance under transformations
  • Learn about convolution in the context of functional analysis and its applications
  • Explore the change of variables theorem in higher dimensions
  • Investigate the role of differential forms in integration and their orientation properties
USEFUL FOR

Mathematicians, students of analysis, and anyone interested in the properties of convolution and measure theory will benefit from this discussion.

psie
Messages
315
Reaction score
40
TL;DR
My textbook claims the convolution is commutative. I think I have found a way to motivate this, but I don't quite understand the textbook's motivation.
I quote;

Throughout this section, we consider the measure space ##(\mathbb R^d,\mathcal B(\mathbb R^d),\lambda)## [##\lambda## being Lebesgue measure]. Let ##f## and ##g## be two real measurable functions on ##\mathbb R^d##. For ##x\in\mathbb R^d##, the convolution $$f\ast g(x)=\int_{\mathbb R^d}f(x-y)g(y)\,\mathrm{d}y$$ is well defined provided $$\int_{\mathbb R^d}|f(x-y)g(y)|\,\mathrm{d}y<\infty.$$In that case, the fact that Lebesgue measure on ##\mathbb R^d## is invariant under translations and under the symmetry ##y\to -y## shows that ##g\ast f(x)## is also well defined and ##g\ast f(x)=f\ast g(x)##.

I struggle with the last sentence and putting the pieces together. I know the abstract change of variables formula for ##\nu## on ##(F,\mathcal D)## being the pushforward measure of ##\mu## on ##(E,\mathcal C)## under ##\varphi:E\to F##, i.e. ##\nu(A)=\mu(\varphi^{-1}(A))## for every ##A\in\mathcal D##. Then for any ##h:F\to\mathbb R##, $$\int_E h(\varphi(x))\,\mu(\mathrm{d}x)=\int_F h(y)\,\nu(\mathrm{d}y).$$I figured that ##h(y)=f(x-y)g(y)## and ##\varphi(x)=x-y##, with ##\mu=\lambda## and ##(E,\mathcal C)=(F,\mathcal D)=(\mathbb R^d,\mathcal B(\mathbb R^d))##. Since Lebesgue measure is invariant under translations, ##\nu## is just Lebesgue measure again. So I get indeed ##f\ast g(x)=g\ast f(x)##. But what do they mean, or what's the relevance of, the invariance under the symmetry ##y\to -y##? And how does one show Lebesgue measure is invariant under this symmetry?
 
Physics news on Phys.org
I think your thoughts are way too complicated. Let ##u=x-y.##
\begin{align*}
(f\ast g)(x)&=\int_{y\in \mathbb{R}^d} f(x-y)g(y)\,dy =- \int_{x-u\in \mathbb{R}^d} f(u)g(x-u) \,du \\[6pt]
&=\int_{u-x\in \mathbb{R}^d} f(u)g(x-u) \,du =\int_{u\in \mathbb{R}^d}g(x-u)f(u) \,du\\[6pt]
&=(g\ast f)(x)
\end{align*}
 
  • Like
Likes   Reactions: psie
fresh_42 said:
\begin{align*}
(f\ast g)(x)&=\int_{y\in \mathbb{R}^d} f(x-y)g(y)\,dy =- \int_{x-u\in \mathbb{R}^d} f(u)g(x-u) \,du \\[6pt]
&=\int_{u-x\in \mathbb{R}^d} f(u)g(x-u) \,du =\int_{u\in \mathbb{R}^d}g(x-u)f(u) \,du\\[6pt]
&=(g\ast f)(x)
\end{align*}
Thank you. :smile:

What did you use in the second equality? In particular $$\int_{y\in \mathbb{R}^d} f(x-y)g(y)\,dy =- \int_{x-u\in \mathbb{R}^d} f(u)g(x-u) \,du.$$ Looks like a change of variables, but I'd expect one to take the absolute value of the determinant, if you look here (note, this is just one of many versions of the change of variables formula in higher dimensions). I don't see where the minus sign would come from, and how it disappears in the third equality.
 
psie said:
Thank you. :smile:

What did you use in the second equality? In particular $$\int_{y\in \mathbb{R}^d} f(x-y)g(y)\,dy =- \int_{x-u\in \mathbb{R}^d} f(u)g(x-u) \,du.$$ Looks like a change of variables, but I'd expect one to take the absolute value of the determinant, if you look here (note, this is just one of many versions of the change of variables formula in higher dimensions). I don't see where the minus sign would come from, and how it disappears in the third equality.
It is a simple change of variables: ##u=x-y## so ##\dfrac{du}{dy}=-1.## I admit that it was a bit lazy. Let me see if I can rephrase it with ##\varphi(y)=x-y## and ##d\varphi(y)=(-1)^d dy## for the ##d##-dimensional case.
\begin{align*}
(f\ast g)(x)&=\int_{y\in \mathbb{R}^d} f(x-y)g(y)\,dy \\[6pt]
&=(-1)^d \int_{x-\varphi(y)\in \mathbb{R}^d} f(\varphi(y))g(x-\varphi(y)) \,d\varphi(y) \\[6pt]
&=(-1)^d\int_{x-u\in \mathbb{R}^d}g(x-u)f(u) \,du\\[6pt]
&=(-1)^d\int_{-u\in \mathbb{R}^d}g(x-u)f(u) \,du\\[6pt]
&=\int_{u\in \mathbb{R}^d}g(x-u)f(u) \,du\\[6pt]
&=(g\ast f)(x)
\end{align*}
The transformation matrix is ##\varphi = -I## with ##\det \varphi=(-1)^d.##

The crucial points are the last two equations:

1. ##x+y## over ##\mathbb{R}^d## covers the same integration range as ##y## does over ##\mathbb{R}^d.## A shift translation by a finite fixed vector does not change the integration of infinite integration limits.

2. Orientation does change the integral, namely by a factor ##\pm 1.## However, it changes the orientation of the differential form as well as the orientation of the integration range. Both cancel each other so that we get commutativity instead of anti-commutativity. I didn't use the transformation theorem for this, only the fact that differential forms build a Grassmann algebra, i.e. that they are oriented. I was lazy once more since I should have written ##dy=dx_1\wedge \ldots \wedge dx_d## and so on.
 
  • Like
Likes   Reactions: psie

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 11 ·
Replies
11
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K