2-D system identification from bispectrum samples

A. David Salvia, Hector M. Valenzuela

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper we consider the problem of modeling 2-D system transfer functions given only bispectrum samples of the noisy output. This identification procedure is a three step process. First, the output bispectrum samples are calculated along a 2-D "slice" in the 4-D bispectrum frequency region. Next, these samples are used to obtain a rational model of the bispectrum slice via a 2-D divided difference approach. Finally, we develop two methods for finding the underlying system transfer function parameters bom this rational model. This system identification procedure is general in that it does not impose causality, recursibility, or minimum phase restrictions on the system to be identified.

Original languageEnglish (US)
Title of host publicationICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages337-340
Number of pages4
ISBN (Electronic)0780305329
DOIs
StatePublished - Jan 1 1992
Event1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States
Duration: Mar 23 1992Mar 26 1992

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
ISSN (Print)1520-6149

Other

Other1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
CountryUnited States
CitySan Francisco
Period3/23/923/26/92

Fingerprint

Transfer functions
Identification (control systems)

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

David Salvia, A., & Valenzuela, H. M. (1992). 2-D system identification from bispectrum samples. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing (pp. 337-340). [226232] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.1992.226232
David Salvia, A. ; Valenzuela, Hector M. / 2-D system identification from bispectrum samples. ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc., 1992. pp. 337-340 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
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David Salvia, A & Valenzuela, HM 1992, 2-D system identification from bispectrum samples. in ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing., 226232, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 3, Institute of Electrical and Electronics Engineers Inc., pp. 337-340, 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992, San Francisco, United States, 3/23/92. https://doi.org/10.1109/ICASSP.1992.226232

2-D system identification from bispectrum samples. / David Salvia, A.; Valenzuela, Hector M.

ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc., 1992. p. 337-340 226232 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - In this paper we consider the problem of modeling 2-D system transfer functions given only bispectrum samples of the noisy output. This identification procedure is a three step process. First, the output bispectrum samples are calculated along a 2-D "slice" in the 4-D bispectrum frequency region. Next, these samples are used to obtain a rational model of the bispectrum slice via a 2-D divided difference approach. Finally, we develop two methods for finding the underlying system transfer function parameters bom this rational model. This system identification procedure is general in that it does not impose causality, recursibility, or minimum phase restrictions on the system to be identified.

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David Salvia A, Valenzuela HM. 2-D system identification from bispectrum samples. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc. 1992. p. 337-340. 226232. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.1992.226232