2004/04/29 by J W C McNabb, J. W. C. McNabb, M Ashley +17 · 3 citations
Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #Gaussian Processes and Bayesian Inference #Meteorological Phenomena and Simulations #Pulsars and Gravitational Waves Research #gr-qc
paper · pdf · doi:10.1088/0264-9381/21/20/013
published as Class.Quant.Grav.21:S1705-S1710,2004 · GWDAW-8 proceedings, 6 pages, 2 figures
arxiv created 2004/04/29 · openalex publication_date 2004/09/29 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
In the search for unmodelled gravitational wave bursts, there are a variety of methods that have been proposed to generate candidate events from time series data. BlockNormal is a method of identifying candidate events by searching for places in the data stream where the characteristic statistics of the data change. These change points divide the data into blocks in which the characteristics of the block are stationary. Blocks in which these characteristics are inconsistent with the long term characteristic statistics are marked as event triggers, which can then be investigated by a more computationally demanding multi-detector analysis.