Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD

Research output: Contribution to conferencePaper

4 Citations (Scopus)
21 Downloads (Pure)

Abstract

We present an algorithm that extracts analytic eigenvalues from a parahermitian matrix. Operating in the discrete Fourier transform domain, an inner iteration re-establishes the lost association between bins via a maximum likelihood sequence detection driven by a smoothness criterion. An outer iteration continues until a desired accuracy for the approximation of the extracted eigenvalues has been achieved. The approach is compared to existing algorithms.
Original languageEnglish
Pages8038-8042
Number of pages5
DOIs
Publication statusPublished - 16 May 2019
Event2019 International Conference on Acoustics, Speech, and Signal Processing - Brighton, United Kingdom
Duration: 12 May 201917 May 2019

Conference

Conference2019 International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP 2019
CountryUnited Kingdom
CityBrighton
Period12/05/1917/05/19

Fingerprint

Bins
Discrete Fourier transforms
Maximum likelihood

Keywords

  • eigenvalues
  • parahermitian matrix
  • algorithm

Cite this

Weiss, S., Proudler, I. K., Coutts, F. K., & Pestana, J. (2019). Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD. 8038-8042. Paper presented at 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom. https://doi.org/10.1109/ICASSP.2019.8682407
Weiss, Stephan ; Proudler, Ian K. ; Coutts, Fraser K. ; Pestana, Jennifer. / Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD. Paper presented at 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom.5 p.
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Weiss, S, Proudler, IK, Coutts, FK & Pestana, J 2019, 'Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD', Paper presented at 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom, 12/05/19 - 17/05/19 pp. 8038-8042. https://doi.org/10.1109/ICASSP.2019.8682407

Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD. / Weiss, Stephan; Proudler, Ian K.; Coutts, Fraser K.; Pestana, Jennifer.

2019. 8038-8042 Paper presented at 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom.

Research output: Contribution to conferencePaper

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AB - We present an algorithm that extracts analytic eigenvalues from a parahermitian matrix. Operating in the discrete Fourier transform domain, an inner iteration re-establishes the lost association between bins via a maximum likelihood sequence detection driven by a smoothness criterion. An outer iteration continues until a desired accuracy for the approximation of the extracted eigenvalues has been achieved. The approach is compared to existing algorithms.

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Weiss S, Proudler IK, Coutts FK, Pestana J. Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD. 2019. Paper presented at 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom. https://doi.org/10.1109/ICASSP.2019.8682407