Reduced search space multiple shift maximum element sequential matrix diagonalisation algorithm

Corr, J and Thompson, K and Weiss, S and Proudler, I K and McWhirter, J G; (2015) Reduced search space multiple shift maximum element sequential matrix diagonalisation algorithm. In: 2nd IET International Conference on Intelligent Signal Processing 2015. IET, GBR, pp. 1-5. ISBN 9781785611360

Preview

Text. Filename: Corr_etal_ISP_2015_multiple_shift_maximum_element_sequential_matrix_diagonalisation.pdf Accepted Author Manuscript Download (161kB)| Preview

Abstract

The Multiple Shift Maximum Element Sequential Matrix Diagonalisation (MSME-SMD) algorithm is a powerful but costly method for performing approximate polynomial eigenvalue decomposition (PEVD) for space-time covariance-type matrices encountered in e.g. broadband array processing. This paper discusses a newly developed search method that restricts the order growth within the MSME-SMD algorithm. In addition to enhanced control of the polynomial degree of the paraunitary and parahermitian factors in this decomposition, the new search method is also computationally less demanding as fewer elements are searched compared to the original while the excellent diagonalisation of MSME-SMD is maintained.

ORCID iDs

Corr, J ORCID: https://orcid.org/0000-0001-9900-0796

Thompson, K ORCID: https://orcid.org/0000-0003-0727-7347

Weiss, S ORCID: https://orcid.org/0000-0002-3486-7206

• Share and Export
  

  RDF+XMLBibTeXRIOXX2 XMLRDF+N-TriplesJSONDublin CoreAtomSimple MetadataReferMETSHTML CitationASCII CitationOpenURL ContextObjectEndNoteOpenURL ContextObject in SpanMODSMPEG-21 DIDLEP3 XMLData Cite XMLRIS (EndNote Online, Zotero, Ref manager, etc)RDF+N3Multiline CSV
• Item metadata

  Item type:	Book Section
  ID code:	60114
  Dates:	Date Event December 2015 Published 2015 Accepted
  Keywords:	multiple shift maximum element, sequential matrix diagonalisation, polynomial matrix eigenvalue decomposition, Electrical Engineering. Electronics Nuclear Engineering, Signal Processing, Electrical and Electronic Engineering
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering Technology and Innovation Centre > Sensors and Asset Management
  Depositing user:	Pure Administrator
  Date deposited:	08 Mar 2017 15:42
  Last modified:	27 Nov 2022 03:48
  URI:	https://strathprints.strath.ac.uk/id/eprint/60114