Capon's Time-Frequency Representation with nonstationary AR autocorrelation

Yariv A. Amos, Joseph Tabrikian, Ilan D. Shallom

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

1 Scopus citations

Abstract

In this paper, a novel approach for spectral analysis of nonstationary signals is presented. For this purpose, the Capon's Time Frequency Representation (CTFR) is employed. It is shown that the CTFR is an upper bound on the range of non-unique solutions for power estimation of a complex sinusoid contaminated with unknown noise. A new local autocorrelation function using a Nonstationary Auto-Regressive (NAR) model is defined and used in the CTFR. This method efficiently models the autocorrelations of NAR processes. Synthetic signals are generated in order to illustrate the superiority of the CTFR with NAR model in comparison to other methods.

Original languageEnglish
Title of host publication2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
PublisherInstitute of Electrical and Electronics Engineers
PagesIV509-IV512
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - 1 Jan 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: 18 Mar 200523 Mar 2005

Publication series

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

Conference

Conference2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period18/03/0523/03/05

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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