Performance trade-offs in sequential matrix diagonalisation search strategies

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

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

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Abstract

Recently a selection of sequential matrix diagonalisation (SMD) algorithms have been introduced which approximate polynomial eigenvalue decomposition of parahermitian matrices. These variants differ only in the search methods that are used to bring energy onto the zero-lag. Here we analyse the search methods in terms of their computational complexities for different sizes of parahermitian matrices which are verified through simulated execution times. Another important factor for these search methods is their ability to transfer energy. Simulations show that the more computationally complex search methods transfer a greater proportion of the off-diagonal energy onto the zero-lag over a selected range of parahermitian matrix sizes. Despite their higher cost per iteration experiments indicate that the more complex search algorithms still converge faster in real time.
Original languageEnglish
Title of host publication2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages25-28
Number of pages4
ISBN (Print)9781479919635
DOIs
Publication statusPublished - 13 Dec 2015
Event6th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015) - Cancun, Mexico
Duration: 13 Dec 201516 Dec 2015

Workshop

Workshop6th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015)
CountryMexico
CityCancun
Period13/12/1516/12/15

Keywords

  • Hermitian matrices
  • computational complexity
  • eigenvalues and eigenfunctions
  • matrix decomposition
  • polynomial approximation
  • search problems
  • algorithm design and analysis
  • approximation algorithms
  • complexity theory
  • covariance matrices
  • real-time systems
  • search methods

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