Multiple shift maximum element sequential matrix diagonalisation for parahermitian matrices

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

Research output: Contribution to conferencePaper

35 Citations (Scopus)
127 Downloads (Pure)

Abstract

A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately using iterative approaches such as the sequential matrix diagonalisation (SMD) algorithm. In this paper, we present an improved SMD algorithm which, compared to existing SMD approaches, eliminates more off-diagonal energy per step. This leads to faster convergence while incurring only a marginal increase in complexity. We motivate the approach, prove its convergence, and demonstrate some results that underline the algorithm's performance.
Original languageEnglish
Pages312-315
Number of pages4
DOIs
Publication statusPublished - Jul 2014
Event2014 IEEE Workshop on Statistical Signal Processing (SSP) - Australia, Gold Coast, United Kingdom
Duration: 29 Jun 20142 Jul 2014

Conference

Conference2014 IEEE Workshop on Statistical Signal Processing (SSP)
CountryUnited Kingdom
CityGold Coast
Period29/06/142/07/14

Keywords

  • parahermitian polynomial matrices
  • SMD algorithm
  • polynomial eigenvalue decomposition

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