PSN-L Email List Message

Subject: Data filtering
From: "Larry Conklin" lconklin@............
Date: Tue, 1 Aug 2000 20:37:15 -0400



John,

The idea had already crossed my mind that it might be interesting to build
some sort of a software digital filter.  I am a retired
electrical-turned-software engineer but don't know much about digital
filtering.  I'd be very interested in any information you could provide me.
I have experimented a little with the filtering capabilities in Winquake on
some of my event files.  A high pass with a 30 second cut-off (ie. .033 hz)
is very effective in cleaning up my data.

Larry

On Tue, 1 Aug 2000, Larry Conklin wrote:
> Second, I routinely see a very long period background noise.  If I run the
> Winquake FFT routine on a "no event" record from my system, I see a broad
> peak around 100 seconds with several spikes in the gram around 60 - 120
> seconds.  I wouldn't be surprised if a lot of this is thermal noise, but
it
> would be nice to know if what I'm seeing is reasonably typical of seismic
> noise.  The noise level does seem lower at night, when there isn't any
> activity in the house.  I understand that there are continuout microseisms
> with a period of around 6 seconds (?).  They aren't obvious in my records,
> perhapse because I don't have the LF gain set high enough.  My LF noise
> level produces peaks that average around 20 or so from a 12 bit A-D
> converter.

Larry,
   One thing not discussed often on the list is digital noise filtering.  If
you have some programming experience, many routines for this type of
filtering
are available for free (especially in fortran).  If you see a time span in
your seismogram that you think might be hiding an event, you can try
filtering
that section of data.  The simplest and most encountered type of noise
filter
is the Weiner filter.  It uses the mathematical idea that the noise and the
untainted signal are not correlated.  The power spectrum of the noise and
the
untainted signal can often be easily estimated from the power spectrum
(modulus squared frequency spectrum) of a digital record.  Knowledge of this
then leads to the construction of the filter, which when applied to the data
can often have amazing results.  If you or anyone else wants more info on
this, let me know and I can post some pdf files describing the numerical
routines and theory.

****************************************************************************
**
John Hernlund
Department of Geological Sciences
Arizona State University
E-mail: hernlund@.......
WWW: http://www.public.asu.edu/~hernlund/
****************************************************************************
**



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Larry Cochrane <cochrane@..............>