Maximum energy sequential matrix diagonalisation for parahermitian matrices

Corr, Jamie and Thompson, Keith and Weiss, Stephan and McWhirter, John G. and Proudler, Ian K.; Matthews, Michael B., ed. (2014) Maximum energy sequential matrix diagonalisation for parahermitian matrices. In: Conference Record of the Forty-Eighth Asilomar Conference on Signals, Systems & Computers. IEEE, USA, pp. 470-474. ISBN 9781479982950

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    Abstract

    Sequential matrix diagonalisation (SMD) refers to a family of algorithms to iteratively approximate a polynomial matrix eigenvalue decomposition. Key is to transfer as much energy as possible from off-diagonal elements to the diagonal per iteration, which has led to fast converging SMD versions involving judicious shifts within the polynomial matrix. Through an exhaustive search, this paper determines the optimum shift in terms of energy transfer. Though costly to implement, this scheme yields an important benchmark to which limited search strategies can be compared. In simulations, multiple-shift SMD algorithms can perform within 10% of the optimum energy transfer per iteration step.

    ORCID iDs

    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.; Matthews, Michael B.
    • Item type:Book Section
      ID code:53321
      Dates:
      Date
      Event
      2014
      Published
      Notes:(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
      Keywords:channel coding, direction-of-arrival estimation, eigenvalues and eigenfunctions, iterative methods, polynomial matrices, precoding, 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:09 Jun 2015 10:18
      Last modified:22 Nov 2021 02:11
      Related URLs:
      URI:https://strathprints.strath.ac.uk/id/eprint/53321
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