Generalized polynomial power method
Khattak, Faizan A. and Proudler, Ian K. and Weiss, Stephan; (2023) Generalized polynomial power method. In: 2023 Sensor Signal Processing for Defence Conference (SSPD). IEEE, GBR. ISBN 9798350337327 (https://doi.org/10.1109/SSPD57945.2023.10257038)
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Abstract
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.
ORCID iDs
Khattak, Faizan A., Proudler, Ian K. and Weiss, Stephan ORCID: https://orcid.org/0000-0002-3486-7206;-
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Item type: Book Section ID code: 86040 Dates: DateEvent22 September 2023Published12 September 2023Published Online23 June 2023AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Telecommunication Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 05 Jul 2023 12:41 Last modified: 03 Oct 2024 00:15 URI: https://strathprints.strath.ac.uk/id/eprint/86040