Adaptive multiresolution for wavelet analysis

dc.creatorSturani, Riccardo
dc.creatorTerenzi, Roberto
dc.date2007-11-02
dc.date.accessioned2026-07-07T11:38:31Z
dc.date.available2026-07-07T11:38:31Z
dc.descriptionWe present a new method of wavelet packet decomposition to be used in gravitational wave detection. An issue in wavelet analysis is what is the time-frequency resolution which is best suited to analyze data when in quest of a signal of unknown shape, like a burst. In the other wavelet methods currently employed, like LIGO WaveBurst, the analysis is performed at some trial resolutions. We propose a decomposition which automatically selects at any frequency the best resolution. The criterion for resolution selection is based on minimization of a function of the data, named entropy in analogy with the information theory. As a qualitative application we show how a multiresolution time-frequency scalogram looks in the case of a sample signal injected over Gaussian noise. For a more quantitative application of the method we tested its efficiency as a non-linear filter of simulated data for burst searches, finding that it is able to lower the false alarm rate of the WaveBurst algorithm with negligible effects on the efficiency.
dc.description8 pages, 4 figures. Proceeding of the 7th Edoardo Amaldi Conference on Gravitational Waves, 8-14 July 2007, Sydney (Australia)
dc.identifierhttps://arxiv.org/abs/0711.0349
dc.identifierhttp://arxiv.org/abs/0711.0349
dc.identifierJ.Phys.Conf.Ser.122:012036,2008
dc.identifierdoi:10.1088/1742-6596/122/1/012036
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/199592
dc.subjectGeneral Relativity and Quantum Cosmology
dc.titleAdaptive multiresolution for wavelet analysis
dc.typetext

Files

Collections