{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:28:02Z","timestamp":1760239682028,"version":"build-2065373602"},"reference-count":86,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T00:00:00Z","timestamp":1606953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004488","name":"Croatian Science Foundation","doi-asserted-by":"publisher","award":["IP-2018-01-3739 and IP-2020-02-4358"],"award-info":[{"award-number":["IP-2018-01-3739 and IP-2020-02-4358"]}],"id":[{"id":"10.13039\/501100004488","id-type":"DOI","asserted-by":"publisher"}]},{"name":"EU Horizon 2020","award":["National Competence Centres in the Framework of EuroHPC 476 (EUROCC)"],"award-info":[{"award-number":["National Competence Centres in the Framework of EuroHPC 476 (EUROCC)"]}]},{"name":"Increasing the Development of New Products and Services Arising from R&amp;D Activities \u2013 Phase II, Operational Programme Competitiveness and Cohesion 2014 - 2020","award":["ABsistemDCiCloud\u201d (KK.01.2.1.02.0179)"],"award-info":[{"award-number":["ABsistemDCiCloud\u201d (KK.01.2.1.02.0179)"]}]},{"name":"University of Rijeka","award":["uniri-tehnic-18-17 and uniri-tehnic-18-15"],"award-info":[{"award-number":["uniri-tehnic-18-17 and uniri-tehnic-18-15"]}]},{"name":"Croatian-Slovenian bilateral project","award":["BI-HR\/20-21-043"],"award-info":[{"award-number":["BI-HR\/20-21-043"]}]},{"name":"European Cooperation in Science and Technology (COST)","award":["CA17137"],"award-info":[{"award-number":["CA17137"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Gravitational-wave data (discovered first in 2015 by the Advanced LIGO interferometers and awarded by the Nobel Prize in 2017) are characterized by non-Gaussian and non-stationary noise. The ever-increasing amount of acquired data requires the development of efficient denoising algorithms that will enable the detection of gravitational-wave events embedded in low signal-to-noise-ratio (SNR) environments. In this paper, an algorithm based on the local polynomial approximation (LPA) combined with the relative intersection of confidence intervals (RICI) rule for the filter support selection is proposed to denoise the gravitational-wave burst signals from core collapse supernovae. The LPA-RICI denoising method\u2019s performance is tested on three different burst signals, numerically generated and injected into the real-life noise data collected by the Advanced LIGO detector. The analysis of the experimental results obtained by several case studies (conducted at different signal source distances corresponding to the different SNR values) indicates that the LPA-RICI method efficiently removes the noise and simultaneously preserves the morphology of the gravitational-wave burst signals. The technique offers reliable denoising performance even at the very low SNR values. Moreover, the analysis shows that the LPA-RICI method outperforms the approach combining LPA and the original intersection of confidence intervals (ICI) rule, total-variation (TV) based method, the method based on the neighboring thresholding in the short-time Fourier transform (STFT) domain, and three wavelet-based denoising techniques by increasing the improvement in the SNR by up to 118.94% and the peak SNR by up to 138.52%, as well as by reducing the root mean squared error by up to 64.59%, the mean absolute error by up to 55.60%, and the maximum absolute error by up to 84.79%.<\/jats:p>","DOI":"10.3390\/s20236920","type":"journal-article","created":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T11:15:43Z","timestamp":1606994143000},"page":"6920","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of the Intersection of Confidence Intervals Rule"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0616-1265","authenticated-orcid":false,"given":"Nikola","family":"Lopac","sequence":"first","affiliation":[{"name":"Faculty of Maritime Studies, University of Rijeka, Studentska 2, 51000 Rijeka, Croatia"},{"name":"Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Radmile Matejcic 2, 51000 Rijeka, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4058-8449","authenticated-orcid":false,"given":"Jonatan","family":"Lerga","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Radmile Matejcic 2, 51000 Rijeka, Croatia"},{"name":"Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6528-3449","authenticated-orcid":false,"given":"Elena","family":"Cuoco","sequence":"additional","affiliation":[{"name":"European Gravitational Observatory (EGO), Cascina, I-56021 Pisa, Italy"},{"name":"Scuola Normale Superiore, Piazza dei Cavalieri, 7-56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"061102","DOI":"10.1103\/PhysRevLett.116.061102","article-title":"Observation of gravitational-waves from a binary black hole merger","volume":"116","author":"Abbott","year":"2016","journal-title":"Phys. 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