Generalized polynomial power method

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)
37 Downloads (Pure)


The polynomial power method repeatedly multiplies a polynomial vector by a para-Hermitian matrix containing spectrally majorised eigenvalue to estimate the dominant eigenvector corresponding the dominant eigenvalue. To limit the order of the resulting vector, truncation is performed in each iteration. This paper extends the polynomial power method from para-Hermitian matrices to a general polynomial matrix for determining its dominant left- and right-singular vectors and the corresponding singular value. The proposed extension assumes that the dominant singular is positive on the unit circle. The resulting algorithm is compared with a state-of-the-art PSVD algorithm and provides better accuracy with reduced computation time and lower approximation orders for the decomposition.
Original languageEnglish
Title of host publication2023 Sensor Signal Processing for Defence Conference (SSPD)
Place of PublicationPiscataway, NJ
Number of pages5
ISBN (Electronic)9798350337327
Publication statusPublished - 22 Sept 2023
Event12th International Conference on Sensor Signal Processing for Defence - Edinburgh, United Kingdom
Duration: 12 Sept 202313 Sept 2023


Conference12th International Conference on Sensor Signal Processing for Defence
Abbreviated titleSSPD'23
Country/TerritoryUnited Kingdom
Internet address


  • polynomial power method
  • polynomial matrices
  • broadband sensor arrays
  • polynomial eigenvalue decomposition (PEVD)


Dive into the research topics of 'Generalized polynomial power method'. Together they form a unique fingerprint.

Cite this