Phase-only information loss

Barry G. Quinn

doi:10.1109/ICASSP.2010.5495779

Phase-only information loss

Barry G. Quinn^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

4 Citations (Scopus)

60 Downloads (Pure)

Abstract

In many areas of signal processing, the phases of complex-valued random variables are used to estimate system parameters, the magnitudes being discarded. In this paper, we consider the implications of doing this: the loss of statistical information and subsequent increase in asymptotic variance. Two particular cases, those of estimating the phase of the mean of a complex distribution, and estimating the frequency of a complex sinusoid in white noise, are considered. The estimators are motivated by estimation under von Mises distributional assumptions. The asymptotic distributional properties are obtained under general assumptions, and are tested using a small number of simulations.

Original language	English
Title of host publication	2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	3982-3985
Number of pages	4
ISBN (Print)	9781424442966
DOIs	https://doi.org/10.1109/ICASSP.2010.5495779
Publication status	Published - 2010
Event	2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States Duration: 14 Mar 2010 → 19 Mar 2010

Other

Other	2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/Territory	United States
City	Dallas, TX
Period	14/03/10 → 19/03/10

Bibliographical note

Copyright 2010 IEEE. Reprinted from Proceedings of ICASSP, the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie Universityâ€™s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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10.1109/ICASSP.2010.5495779

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title = "Phase-only information loss",

abstract = "In many areas of signal processing, the phases of complex-valued random variables are used to estimate system parameters, the magnitudes being discarded. In this paper, we consider the implications of doing this: the loss of statistical information and subsequent increase in asymptotic variance. Two particular cases, those of estimating the phase of the mean of a complex distribution, and estimating the frequency of a complex sinusoid in white noise, are considered. The estimators are motivated by estimation under von Mises distributional assumptions. The asymptotic distributional properties are obtained under general assumptions, and are tested using a small number of simulations.",

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Quinn, BG 2010, Phase-only information loss. in 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings., 5495779, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 3982-3985, 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, Dallas, TX, United States, 14/03/10. https://doi.org/10.1109/ICASSP.2010.5495779

Phase-only information loss. / Quinn, Barry G.
2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2010. p. 3982-3985 5495779.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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Phase-only information loss

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