Computational and numerical properties of a broadband subspace-based likelihood ratio test
Pahalson, Cornelius Allamis Dawap and Crockett, Louise Helen and Weiss, Stephan (2024) Computational and numerical properties of a broadband subspace-based likelihood ratio test. In: IEEE High Performance Extreme Computing Conference, 2024-09-23 - 2024-09-27. (In Press)
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Abstract
This paper investigates the performance of a likelihood ratio test in combination with a polynomial subspace projection approach to detect weak transient signals in broadband array data. Based on previous empirical evidence that a likelihood ratio test is advantageously applied in a lower-dimensional subspace, we present analysis that highlights how the polynomial subspace projection whitens a crucial part of the signals, enabling a detector to operate with a shortened temporal window. This reduction in temporal correlation, together with a spatial compaction of the data, also leads to both computational and numerical advantages over a likelihood ratio test that is directly applied to the array data. The results of our analysis are illustrated by examples and simulations.
ORCID iDs
Pahalson, Cornelius Allamis Dawap, Crockett, Louise Helen and Weiss, Stephan ORCID: https://orcid.org/0000-0002-3486-7206;-
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Item type: Conference or Workshop Item(Paper) ID code: 90522 Dates: DateEvent2024Published2024AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 09 Sep 2024 12:56 Last modified: 03 Oct 2024 10:02 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/90522