Conference item

Symmetric polynomial & CRT based algorithms for multiple frequency determination from undersampled waveforms

Abstract:: Frequency estimation, especially with sampling rates below the Nyquist rate, has abundant applications in engineering. Recently, Chinese remainder theorem(CRT)-based frequency reconstruction from undersampled complex-value waveforms becomes one of the frontier focuses in the fields of signal processing, electromagnetism and optics etc. In this paper, we present several CRT-based algorithms for determining multiple frequencies via symmetric polynomials. The computational complexity of these algorithms is in the polynomial class (P).

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Xiao, H., Cremers, C., & Garg, H. (2017). Symmetric polynomial & CRT based algorithms for multiple frequency determination from undersampled waveforms. 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, DC, USA, 7-9 Dec. 2016, 202–206.

MLA Style

Xiao, H., et al. “Symmetric Polynomial CRT Based Algorithms for Multiple Frequency Determination from Undersampled Waveforms.” 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, DC, USA, 7-9 Dec. 2016, Institute of Electrical and Electronics Engineers, 2017, pp. 202–06.

Chicago Style

Xiao, H, C Cremers, and H Garg. 2017. “Symmetric Polynomial CRT Based Algorithms for Multiple Frequency Determination from Undersampled Waveforms.” In 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, DC, USA, 7-9 Dec. 2016, 202–6. Institute of Electrical and Electronics Engineers.
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Files:: CRT-frequency-hanshen.pdf

(Preview, Accepted manuscript, pdf, 213.4KB, Terms of use)

Publisher copy:: 10.1109/GlobalSIP.2016.7905832

Authors

+ Xiao, H More by this author

Role:: Author

+ Cremers, C More by this author

Institution:: University of Oxford
Division:: Societies, Other & Subsidiary Companies
Department:: Kellogg College
Oxford college:: Kellogg College
Role:: Author

+ Garg, H More by this author

Role:: Author

Publisher:: Institute of Electrical and Electronics Engineers
Host title:: 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, DC, USA, 7-9 Dec. 2016
Journal:: 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP) More from this journal
Pages:: 202-206
Publication date:: 2017-04-24
Acceptance date:: 2016-08-05
DOI:: 10.1109/GlobalSIP.2016.7905832
ISBN:: 9781509045457

Pubs id:: pubs:698162
UUID:: uuid:fc0a96ce-cb08-4ed3-9fa7-81dd8094bacb
Local pid:: pubs:698162
Source identifiers:: 698162
Deposit date:: 2017-06-14

Terms of use

Copyright holder:: © IEEE 2016
Copyright date:: 2017
Notes:: This is the author accepted manuscript following peer review version of the article. The final version is available online from IEEE at: 10.1109/GlobalSIP.2016.7905832

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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