Smooth QR decomposition of polynomial matrices

Research output: Contribution to conferencePaperpeer-review

16 Downloads (Pure)

Abstract

This paper presents a novel algorithm for determining a compact order QR decomposition of a polynomial matrix, where both the Q and R factors themselves are approximated by polynomial matrices. The QR factorisation is subject to an allpass ambiguity; existing time domain methods can lead to factorisations of high order. The proposed algorithm performs the conventional QR decomposition the discrete Fourier transform domain. Subsequently, it establishes phase coherence between adjacent bins through a phase smoothing procedure, aimed at obtaining compact-order factors. The method is validated through experiments over an ensemble of randomized polynomial matrices and shown to outperform state-of-the-art algorithms.
Original languageEnglish
Pages1-5
Number of pages5
Publication statusPublished - 13 Dec 2023
Event9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - Los Suenos, Costa Rica
Duration: 10 Dec 202313 Dec 2023
https://camsap23.ig.umons.ac.be/

Workshop

Workshop9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Abbreviated titleCAMSAP
Country/TerritoryCosta Rica
CityLos Suenos
Period10/12/2313/12/23
Internet address

Keywords

  • QR decomposition
  • polynomial matrix
  • Fourier transform

Fingerprint

Dive into the research topics of 'Smooth QR decomposition of polynomial matrices'. Together they form a unique fingerprint.

Cite this