Abstract
Extracting analytic eigenvectors from parahermitian matrices relies on phase smoothing in the discrete Fourier transform (DFT) domain as its most expensive algorithmic component. Some algorithms require an a priori estimate of the eigenvector support and therefore the DFT length, while others iteratively increase the DFT. Thus in this document, we aim to complement the former and to reduce the computational load of the latter by estimating the time-domain support of eigenvectors. The proposed approach is validated via an ensemble of eigenvectors of known support, which the estimated support accurately matches.
Original language | English |
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Pages | 1-6 |
Number of pages | 6 |
Publication status | Published - 20 Oct 2022 |
Event | International Conference on Recent Advances in Electrical Engineering and Computer Sciences - Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan Duration: 18 Oct 2022 → 20 Oct 2022 http://raeecs22.pieas.edu.pk/ |
Conference
Conference | International Conference on Recent Advances in Electrical Engineering and Computer Sciences |
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Abbreviated title | RAEE |
Country/Territory | Pakistan |
City | Islamabad |
Period | 18/10/22 → 20/10/22 |
Internet address |
Keywords
- discrete Fourier transform (DFT)
- eigenvectors
- algorithms
- time-domain support
- computational load