Cyclic-by-row approximation of iterative polynomial EVD algorithms

Corr, Jamie and Thompson, Keith and Weiss, Stephan and McWhirter, John G. and Proudler, Ian K.; (2014) Cyclic-by-row approximation of iterative polynomial EVD algorithms. In: Sensor Signal Processing for Defence (SSPD), 2014. IEEE, GBR, pp. 1-5. ISBN 978-1-4799-5294-6

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    Abstract

    A recent class of sequential matrix diagonalisation (SMD) algorithms have been demonstrated to provide a fast converging solution to iteratively approximating the polynomial eigenvalue decomposition of a parahermitian matrix. However, the calculation of an EVD, and the application of a full unitary matrix to every time lag of the parahermitian matrix in the SMD algorithm results in a high numerical cost. In this paper, we replace the EVD with a limited number of Givens rotations forming a cyclic-by-row Jacobi sweep. Simulations indicate that a considerable reduction in computational complexity compared to SMD can be achieved with a negligible sacrifice in diagonalisation performance, such that the benefits in applying the SMD are maintained.

    Creators(s): Corr, Jamie ORCID logoORCID: https://orcid.org/0000-0001-9900-0796, Thompson, Keith ORCID logoORCID: https://orcid.org/0000-0003-0727-7347, Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206, McWhirter, John G. and Proudler, Ian K.;
    Item type:Book Section
    ID code:53354
    Keywords:computational complexity reduction, Jacobi sweep, sequential matrix diagonalisation algorithms, eigenvalues and eigenfunctions, iterative methods, signal processing, Electrical engineering. Electronics Nuclear engineering, 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:12 Jun 2015 08:46
    Last modified:20 Jan 2021 15:43
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/53354
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