What is the Integral of x^{2} e^{-x^2} dx in Signal Processing?

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Discussion Overview

The discussion revolves around the integral of the function \( x^{2} e^{-x^{2}} \) over the entire real line, specifically in the context of signal processing. Participants explore various methods for evaluating this integral, including integration by parts, the use of the error function, and properties of Gaussian integrals.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant, Niks, expresses difficulty in proceeding with integration by parts due to the non-elementary nature of the integral of \( e^{-x^{2}} \).
  • Another participant suggests that the integral can be expressed in terms of the error function, \( \text{Erf}(x) \).
  • Some participants discuss the importance of including limits when performing integration by parts, noting that the definite integral is more straightforward than the indefinite integral.
  • A participant mentions a formula involving the Gamma function for the definite integral of \( x^{n} e^{-x^{2}} \), indicating it can be proven by induction.
  • Another participant proposes using a differentiation technique related to Gaussian integrals, suggesting it may simplify the evaluation.
  • There is a mention of using Leibniz's rule as a potentially simpler method for this integral.
  • One participant provides an expression derived through substitutions and integration by parts, although they express frustration with formatting their derivation.
  • Another participant notes that the integral can be related to the variance of a Gaussian random variable, which may be relevant in the context of signal processing.

Areas of Agreement / Disagreement

Participants do not reach a consensus on a single method for evaluating the integral, with multiple approaches and viewpoints presented. Some methods are favored by certain participants, while others remain contested.

Contextual Notes

There are unresolved aspects regarding the assumptions made in various approaches, particularly concerning the use of limits and the nature of the functions involved in integration by parts.

Who May Find This Useful

This discussion may be useful for individuals interested in mathematical techniques for evaluating integrals, particularly in the context of signal processing and related fields.

niks
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I ran into an integral while working on response of a signal processing filter, it looks like:

\int_{-\infty}^{\infty} x^{2} e^{-x^{2}} dx

While trying integration by parts u = x^{2} we get du = 2xdx but can't proceed with dv = e^{-x^{2}} because then
v = \int e^{-x^{2}}
can't be integrated unless we use the limits.

Can anyone suggest an approach for this?

Thanks,
Niks
 
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What exactly are you trying to do? As you point out, your v is not any elementary function, and that tells you that neither is
\int x^2e^{-x^2} dx
You might be able to do that in terms of the "error function", Erf(x), which is defined to be
\int e^{-x^2} dx
 
If you just want to calculate the definite integral, I don't see why you wouldn't want to include the limits when integrating by parts?
 
His point, about the limits of integration, was that it is well known that
\int_{-\infty}^{\infty} e^{x^2}dx= 2\sqrt{\pi}[/itex]<br /> while the anti-derivative is not an elementary function. in other words, he could, theoretically, do it as a definite integral with the right limits but not as an indefinite integral.
 
Was that adressed to me?

Anyway, Maple tells me that:
<br /> \int_{-\infty}^{\infty} x^{n} e^{-x^{2}}\rm{d} x=\frac{1}{2}\Gamma\left(\frac{n}{2}+\frac{1}{2}\right)\left(1+(-1)^n\right) <br /> ,
which should be possible to prove by induction.

PS. HallsofIvy: You have forgotten the minus-sign in your integrand.
 
A cute way to solve this is to recall that

\int_{-\infty}^{\infty}e^{-ax^2}=\frac{\sqrt{\pi}}{\sqrt{a}}

Then use Feynman's favorite trick and differentiate both sides with respect to a, and evaluate at a = 1.
 
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HallsofIvy said:
His point, about the limits of integration, was that it is well known that
\int_{-\infty}^{\infty} e^{x^2}dx= 2\sqrt{\pi}[/itex]<br /> while the anti-derivative is not an elementary function. in other words, he could, theoretically, do it as a definite integral with the right limits but not as an indefinite integral.
<br /> For one, it&#039;s e^{-x^2} and for two, it&#039;s \sqrt{\pi}.
 
As you point out, your v is not any elementary function,
I think I should use this as a guideline for future problems. Both u and v should be elementary functions otherwise integration by parts becomes too messy(perhaps impossible).

while the anti-derivative is not an elementary function. in other words, he could, theoretically, do it as a definite integral with the right limits but not as an indefinite integral.
Yes, that was what I had in mind. That's why I got stuck there.

Anyway, Maple tells me that:
<br /> <br /> \int_{-\infty}^{\infty} x^{n} e^{-x^{2}}\rm{d} x=\frac{1}{2}\Gamma\left(\frac{n}{2}+\frac{1}{2}\r ight)\left(1+(-1)^n\right) <br /> <br />
which should be possible to prove by induction.
Thanks! That will help me move forward.

Thanks to everyone who replied, I learned a lot from this thread.

-Niks
 
Using lots of substitutions and integration by parts I get this:

\int x^{2}e^{-{x^2}}dx=xe^{x^{2}}\left[1-\sum_{n=1}^{\infty}\frac{\prod_{k=2}^{n}\left(2k-3\right)}{2^{n}x^{2n}}\right]

I would go over the derivation but LaTex is killing me.
 
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Quite frankly, I think using Leibniz' rule, as suggested by Nicksauce, would by far be the simplest method in this case.
 
  • #11
Quite frankly, I think using Leibniz' rule, as suggested by Nicksauce, would by far be the simplest method in this case.

Quite true.

But, if doing by parts, then the proper selection of u an dv is

u=x

dv= x*e^{-x^2}dx

and then things won't be so messy - however, it will involve the definite integral \int^{\infty}_{-\infty}{ e^{-{x^2}}dx} which we know equals \sqrt{\pi}.
 
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  • #12
umm mathematica gives me \frac{\sqrt{\pi}}{2}

and for the indefinite :

<br /> \frac{1}{4} \sqrt{\pi } \text{erf}(x)-\frac{1}{2} e^{-x^2} x<br />
 
  • #13
Well, perhaps the very simplest approach is to recognize that the integral is \sqrt{\pi} times the variance of a Gaussian random variable with mean 0 and standard deviation \frac{1}{\sqrt{2}}. That's certainly all I'd bother doing in the signal processing context the OP mentioned.
 

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