Next: Function: splitup()
Up: GRASP Routines: Gravitational Radiation
Previous: Vetoing techniques ( time/frequency
Contents
In Section we have derived the statistical properties of
the test, and described it in mathematical terms. This is a
bit deceptive, because this test was actually developed based on some
simple physical intuition. We noticed with experience that many of the
high SNR events that were not found by the outlier is_gaussian()
test did not sound anything like chirps (when listened to with the audio() and sound() functions). It was clear from just listening
that for these spurious signals did not have the low frequency signal
arriving first, followed by the high frequency signal arriving last,
in the same way as a chirp signal. So in fact the test was
designed to discriminate the way in which the different frequencies
arrived with time. In effect, the filter used to construct the signal
passes only the lowest frequencies, the filter used to construct
the signal passes the nexttolowest frequencies, and so on.
The filter which produces the signal passes the highest range of
frequencies which would make a significant contribution (i.e. a fraction
) of the SNR for a true chirp.
If the signal is a true chirp, then the outputs of each of these different
filters (the may be thought of as functions of lag )
all peak at the same timeoffset , the same timeoffset that
maximizes the total signal . This is illustrated in Figure .
Figure:
This figure shows the output of four singlephase filters for the
case, for a ``true chirp" injected into a stream of real IFO data
(left set of figures) and a transient noise burst already present in
another stream of real IFO data (right set of figures). When a true
chirp is present, the filters in the different frequency bands all peak
at the same time offset : the time offset which maximizes the SNR.
At this instant in time, all of the are about the same value.
However when the filter was triggered by a nonchirp signal, the filters
in the different frequency bands peak at different times, and in fact
at time they have very different values (some large, some small,
and so on).

It is also instructive to compare the values of the filter
outputs (singlephase test) for the two cases shown in Figure
. For the injected chirp, the signaltonoise ratio
was 9.2, and the signal values in the different bands were
so there is a large probability of having this large.
For the spurious noise event shown in Figure the
SNR was quite similar (8.97) but the value of is very different:
so the probability that this value of would be obtained for a chirp
plus Gaussian noise is extremely small.
Next: Function: splitup()
Up: GRASP Routines: Gravitational Radiation
Previous: Vetoing techniques ( time/frequency
Contents
Bruce Allen
20001119