Computer Science – Performance
Scientific paper
Mar 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004cqgra..21s.801c&link_type=abstract
Classical and Quantum Gravity, Volume 21, Issue 5, pp. S801-S806 (2004).
Computer Science
Performance
1
Scientific paper
We investigate the possibility of improving the detection efficiency for deterministic gravitational wave signals in the presence of non-stationary noise. The proposed method is based on an adaptive whitening procedure to be applied to the experimental data, and depends on a 'forgetting factor' parameter λ. We test the method on simulated data, and show that by choosing λ appropriately it is possible to reduce the non-stationarity noise of the time series and to implement a detector which approaches the performances of the optimal Wiener filter for a deterministic signal in the presence of non-stationary noise of known Gaussian statistic.
Cella Giancarlo
Cuoco Elena
Guidi Gianluca M.
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