Computational and numerical properties of a broadband subspace-based likelihood ratio test

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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 ORCID logoORCID: https://orcid.org/0000-0003-4436-0254 and Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206;
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