Nasty Autocorrelation Integral

In summary, the person is asking for advice on how to solve an autocorrelation integral. They are an expert in complex analysis and calculus, but are not an expert in Fourier transforms. They have tried solving the problem the old fashioned way and it turned out better than they thought. However, they don't think that \tau can be solved for explicitly.
  • #1
krobben92
6
0
Hi guys,

Long story short, I need to compute an autocorrelation integral. Here's the problem:

There are two arbitrary gaussian pulses, one following the other by a fixed distance. By computing the autocorrelation over space(not time) and taking the derivative of the space-shift autocorrelation and setting it equal to zero, important information hopefully could be obtained.

The mathematics of this would be as followed:
[itex]\frac{\partial}{\partial\tau}\int_{-\infty}^{\infty}(Ae^{-a(x-c)^2}+Be^{-b(x-d)^2})(Ae^{-a(x-c-\tau)^2}+Be^{-b(x-d-\tau)^2})dx=0[/itex]
[itex]\int_{-\infty}^{\infty}(Ae^{-a(x-c)^2}+Be^{-b(x-d)^2})(a(x-c-\tau)Ae^{-a(x-c-\tau)^2}+b(x-d-\tau)Be^{-b(x-d-\tau)^2})dx=0[/itex]

I am NOT asking anyone to do this for me - I'll do it myself but I just need some ideas or directions on how to go about it.
I have experience in Fourier transforms, complex analysis and calculus of course. I've considered doing a complex contour integral but I'm not sure how reasonable that is after seeing how big of a pain the normal gaussian contour integral is. I've considered Fourier transforms a little - I didn't immediately see much help due to the Fourier transform of a gaussian just being another gaussian. I've thought about parametrization or even centering the integral about the center of the two gaussians but I don't know where to start I guess.

It's clearly a bound integral but is it just too impossibly hard to try?
 
Last edited:
Physics news on Phys.org
  • #2
You can reduce the problem to several integrals of the types ##\int dx e^{-(x+d)^2 - (x-d)^2}##, ##\int dx x e^{-(x+d)^2 - (x-d)^2}## and maybe something I missed and look for solution methods for those integrals.
 
  • #3
Yes, that's definitely one way to do it. However, this may take a couple dozen sheets of paper and a few hours considering the factoring. I guess after seeing so many tricks in math classes I just assumed there might be a quick way around this... But real world problems versus classroom problems aren't a fair comparison I suppose.
 
  • #4
Well I tried it the old fashion way and it turned out better than I thought - but I don't think [itex]\tau[/itex] can be solved for explicitly.

[itex]\frac{-A^{2}}{2\sqrt{2a}}e^{\frac{-a\tau^{2}}{2}}+\frac{-B^{2}}{2\sqrt{2b}}e^{\frac{-b\tau^{2}}{2}} = \frac{2ABe^{\frac{-ab(j(j-2k)+k^{2})}{a+b}}}{(a+b)\sqrt{a+b}}e^{\frac{-ab\tau^{2}}{a+b}}(\tau cosh(\frac{2ab\tau(j-k)}{a+b})-(j-k)sinh(\frac{2ab\tau(j-k)}{a+b}))[/itex]

Any other ideas? I'm not an expert on Fourier transforms but I'm beginning to think that's the only way because it should be a multi-valued answer - just not sure how to approach it.
 
Last edited:

What is "Nasty Autocorrelation Integral"?

"Nasty Autocorrelation Integral" is a mathematical term used in signal processing to describe the correlation between a signal and a delayed version of itself.

Why is it called "nasty"?

It is called "nasty" because it is notoriously difficult to calculate and can produce misleading or incorrect results if not properly accounted for.

What causes "Nasty Autocorrelation Integral"?

"Nasty Autocorrelation Integral" is caused by the presence of autocorrelated noise in a signal, which can be caused by a variety of factors such as imperfect instrumentation or environmental interference.

How does "Nasty Autocorrelation Integral" affect signal processing?

If not properly accounted for, "Nasty Autocorrelation Integral" can distort or mask important features of a signal, making it difficult to accurately analyze or interpret data.

What methods are used to deal with "Nasty Autocorrelation Integral"?

There are various methods that can be used to mitigate the effects of "Nasty Autocorrelation Integral", such as removing or filtering out the autocorrelated noise, using specialized algorithms, or carefully adjusting the signal processing parameters.

Similar threads

Replies
4
Views
753
Replies
31
Views
930
Replies
19
Views
3K
Replies
3
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
161
Replies
1
Views
939
Replies
21
Views
823
  • Calculus
Replies
1
Views
1K
Replies
2
Views
294
Replies
3
Views
1K
Back
Top