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

Research output: Contribution to conferencePaperpeer-review

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.
Original languageEnglish
Pages1-7
Number of pages7
Publication statusAccepted/In press - 2024
EventIEEE High Performance Extreme Computing Conference - Waltham, MA, United States
Duration: 23 Sept 202427 Sept 2024
https://ieee-hpec.org/

Conference

ConferenceIEEE High Performance Extreme Computing Conference
Abbreviated titleHPEC'24
Country/TerritoryUnited States
CityWaltham, MA
Period23/09/2427/09/24
Internet address

Keywords

  • transient signals
  • broadband array

Fingerprint

Dive into the research topics of 'Computational and numerical properties of a broadband subspace-based likelihood ratio test'. Together they form a unique fingerprint.

Cite this