Causality-constrained multiple shift sequential matrix diagonalisation for parahermitian matrices

Jamie Corr, Keith Thompson, Stephan Weiss, John G. McWhirter, Ian K. Proudler

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

12 Citations (Scopus)

Abstract

This paper introduces a causality constrained sequential matrix diagonalisation (SMD) algorithm, which generates a causal paraunitary transformation that approximately diagonalises and spectrally majorises a parahermitian matrix, and can be used to determine a polynomial eigenvalue decomposition. This algorithm builds on a multiple shift technique which speeds up diagonalisation per iteration step based on a particular search space, which is constrained to permit a maximum number of causal time shifts. The results presented in this paper show the performance in comparison to existing algorithms, in particular an unconstrained multiple shift SMD algorithm, from which our proposed method derives.
Original languageEnglish
Title of host publication2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)
PublisherIEEE
Pages1277-1281
Number of pages5
ISBN (Print)978-0-9928626-1-9
Publication statusPublished - Sep 2014
Event22nd European Signal Processing Conference - Lisbon Congress Centre, Lisbon, Portugal
Duration: 1 Sep 20145 Sep 2014
Conference number: 2014

Conference

Conference22nd European Signal Processing Conference
Abbreviated titleEUSIPCO
CountryPortugal
CityLisbon
Period1/09/145/09/14

Keywords

  • eigenvalues and eigenfunctions
  • iterative methods
  • matrix decomposition
  • causal paraunitary transformation
  • causal time shifts

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