Drexel dragonThe Math ForumDonate to the Math Forum



Search All of the Math Forum:

Views expressed in these public forums are not endorsed by Drexel University or The Math Forum.


Math Forum » Discussions » sci.math.* » sci.math.num-analysis.independent

Topic: Iterative Match Filterings
Replies: 33   Last Post: Apr 17, 2012 6:13 PM

Advanced Search

Back to Topic List Back to Topic List Jump to Tree View Jump to Tree View   Messages: [ Previous | Next ]
BretCahill@peoplepc.com

Posts: 487
Registered: 6/24/08
Re: Iterative Match Filterings
Posted: Apr 5, 2012 12:27 PM
  Click to see the message monospaced in plain text Plain Text   Click to reply to this topic Reply

> >>>> Because if you ain't applying a filter to the purpose for which it is
> >>>> designed

>
> >>> If you can't figure out how to use convolutions and match filtering to
> >>> determine magnitudes of noisy signals you need to start a thread
> >>> entitled "A Scholarly Enumeration of Filters&    Their Purposes."

>
> >>> Maybe you can get it in Wikipedia!
>
> >>> Bret Cahill
>
> >> Wiki is a bit weak on iterative deconvolution algorithms.
>
> >> The sort of thing you are asking about, or rather a version that
> >> actually works in practice was invented in 1974 by Hogbom as the CLEAN
> >> algorithm for radio astronomy. His original paper is online at:

>
> >>http://www.astro.rug.nl/~vdhulst/SignalProcessing/Project1_data/clean...
>
> >> Variants of this algorithm are still used today in aperture synthesis
> >> although I prefer other deconvolution algorithms myself.

>
> > In match filtering the deconvolution step to recover the original
> > [filtered]wave form isn't complicated.  Just take the square root in
> > the frequency domain, IMSQRT in Excel.

>
> Anyone who says deconvolution isn't complicated demonstrably does not
> have the first clue about the subject of signal processing.


The issue here is the special kind of convolution used in match
filtering.

If you want to change the issue to convolutions generally feel free to
start another thread.

> Convolution
> is easy but deconvolution is usually


Yea, _usually_.

Does this include the convolution of a function with itself?

Remember, no dodging.

> a very difficult inverse problem.

Unless the convolution is of a signal with a kernel or a kernel with
itself.

In that case the deconvolution just requires taking the square root in
the frequency domain.

> > Of course, if the magnitude of the kernel is different than the
> > magnitude of the signal -- the general case -- then the magnitude of
> > the recovered signal will be the sqrt of the product of the 2
> > magnitudes.


> > If you want to get the original magnitude of the signal just square
> > the mag. of the filtered signal and then divide by the mag. of the
> > kernel, or, to keep errors equal, divide by the kernel match filtered
> > with itself.

>
> > This was done 7 decades ago, wasn't it?
>
> Your description is so vague and woolly that


that anyone with an even a junior level applied math background should
be able to show it on Excel.

WARNING: THIS MAY ALREADY BE ON A LINK SOMEWHERE! STOP DIGGING AND
START GOOGLING!


Bret Cahill






Date Subject Author
4/4/12
Read Re: Iterative Match Filterings
Tim Wescott
4/4/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/5/12
Read Re: Iterative Match Filterings
Martin Brown
4/5/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/5/12
Read Re: Iterative Match Filterings
Martin Brown
4/5/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/5/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/5/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/5/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/5/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/6/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/6/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/6/12
Read Re: Iterative Match Filterings
robert bristow-johnson
4/6/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
robert bristow-johnson
4/6/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/6/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/6/12
Read Re: Iterative Match Filterings
Eric Jacobsen
4/7/12
Read Re: Iterative Match Filterings
BretCahill@peoplepc.com
4/5/12
Read Re: Iterative Match Filterings
glen herrmannsfeldt
4/15/12
Read Re: Iterative Match Filterings
Bret Cahill
4/15/12
Read ...
bulegoge@columbus.rr.com
4/17/12
Read Iterative Match Filterings
Bret Cahill
4/17/12
Read ...
bulegoge@columbus.rr.com
4/17/12
Read Re: ...
glen herrmannsfeldt
4/17/12
Read Easy Deconvolution of Match Filter Output
Bret Cahill
4/17/12
Read Re: Easy Deconvolution of Match Filter Output
bulegoge@columbus.rr.com
4/17/12
Read ...
bulegoge@columbus.rr.com
4/17/12
Read ...
bulegoge@columbus.rr.com

Point your RSS reader here for a feed of the latest messages in this topic.

[Privacy Policy] [Terms of Use]

© Drexel University 1994-2014. All Rights Reserved.
The Math Forum is a research and educational enterprise of the Drexel University School of Education.