On fitting exponentially damped sinusoids

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

    Abstract

    There is an enormous literature associated with the estimation of the parameters of a sinusoid in additive noise. While there has been less work devoted to the estimation of the parameters of noisy sinusoids with exponentially damped amplitudes, the two problems have equally long histories, with a common solution proposed by Prony in 1795 [1]. Most of the modern approaches to the problem involve the use of sample autocovariances. In this paper, we review the nonlinear regression based approaches, and describe and analyse a 'frequency-domain' approach that is inherently much more accurate than the covariance-based approach, but which is also computationally efficient, extending the work of Aboutanios [2].

    LanguageEnglish
    Title of host publication2014 IEEE Workshop on Statistical Signal Processing, SSP 2014
    Place of PublicationPiscataway, NJ
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages201-204
    Number of pages4
    ISBN (Print)9781479949755
    DOIs
    Publication statusPublished - 2014
    Event2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 - Gold Coast, QLD, Australia
    Duration: 29 Jun 20142 Jul 2014

    Other

    Other2014 IEEE Workshop on Statistical Signal Processing, SSP 2014
    CountryAustralia
    CityGold Coast, QLD
    Period29/06/142/07/14

    Fingerprint

    Damped
    Autocovariance
    Nonlinear Regression
    Additive noise
    Additive Noise
    Frequency Domain
    Review
    History

    Cite this

    Quinn, B. G. (2014). On fitting exponentially damped sinusoids. In 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 (pp. 201-204). [6884610] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SSP.2014.6884610
    Quinn, Barry G. / On fitting exponentially damped sinusoids. 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 201-204
    @inproceedings{2a3c2bd871bf47c9a83be11a0de7b3dd,
    title = "On fitting exponentially damped sinusoids",
    abstract = "There is an enormous literature associated with the estimation of the parameters of a sinusoid in additive noise. While there has been less work devoted to the estimation of the parameters of noisy sinusoids with exponentially damped amplitudes, the two problems have equally long histories, with a common solution proposed by Prony in 1795 [1]. Most of the modern approaches to the problem involve the use of sample autocovariances. In this paper, we review the nonlinear regression based approaches, and describe and analyse a 'frequency-domain' approach that is inherently much more accurate than the covariance-based approach, but which is also computationally efficient, extending the work of Aboutanios [2].",
    author = "Quinn, {Barry G.}",
    year = "2014",
    doi = "10.1109/SSP.2014.6884610",
    language = "English",
    isbn = "9781479949755",
    pages = "201--204",
    booktitle = "2014 IEEE Workshop on Statistical Signal Processing, SSP 2014",
    publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
    address = "United States",

    }

    Quinn, BG 2014, On fitting exponentially damped sinusoids. in 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014., 6884610, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 201-204, 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014, Gold Coast, QLD, Australia, 29/06/14. https://doi.org/10.1109/SSP.2014.6884610

    On fitting exponentially damped sinusoids. / Quinn, Barry G.

    2014 IEEE Workshop on Statistical Signal Processing, SSP 2014. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 201-204 6884610.

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

    TY - GEN

    T1 - On fitting exponentially damped sinusoids

    AU - Quinn, Barry G.

    PY - 2014

    Y1 - 2014

    N2 - There is an enormous literature associated with the estimation of the parameters of a sinusoid in additive noise. While there has been less work devoted to the estimation of the parameters of noisy sinusoids with exponentially damped amplitudes, the two problems have equally long histories, with a common solution proposed by Prony in 1795 [1]. Most of the modern approaches to the problem involve the use of sample autocovariances. In this paper, we review the nonlinear regression based approaches, and describe and analyse a 'frequency-domain' approach that is inherently much more accurate than the covariance-based approach, but which is also computationally efficient, extending the work of Aboutanios [2].

    AB - There is an enormous literature associated with the estimation of the parameters of a sinusoid in additive noise. While there has been less work devoted to the estimation of the parameters of noisy sinusoids with exponentially damped amplitudes, the two problems have equally long histories, with a common solution proposed by Prony in 1795 [1]. Most of the modern approaches to the problem involve the use of sample autocovariances. In this paper, we review the nonlinear regression based approaches, and describe and analyse a 'frequency-domain' approach that is inherently much more accurate than the covariance-based approach, but which is also computationally efficient, extending the work of Aboutanios [2].

    UR - http://www.scopus.com/inward/record.url?scp=84907394937&partnerID=8YFLogxK

    U2 - 10.1109/SSP.2014.6884610

    DO - 10.1109/SSP.2014.6884610

    M3 - Conference proceeding contribution

    SN - 9781479949755

    SP - 201

    EP - 204

    BT - 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014

    PB - Institute of Electrical and Electronics Engineers (IEEE)

    CY - Piscataway, NJ

    ER -

    Quinn BG. On fitting exponentially damped sinusoids. In 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 201-204. 6884610 https://doi.org/10.1109/SSP.2014.6884610