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dc.contributor.authorRodríguez Fonollosa, José Adrián
dc.contributor.authorMasgrau Gómez, Enrique José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.identifier.citationFonollosa, José A. R., Masgrau, E. Adaptive system identification based on higher-order statistics. A: IEEE International Conference on Acoustics, Speech, and Signal Processing. "International Conference on Acoustics, Speech and Signal Processing 1991". Toronto, Ontario: 1991, p. 3437-3440.
dc.description.abstractThe problem of estimating the autoregressive (AR) parameters of a causal AR moving average (ARMA) (p,q) process using higher-order statistic is addressed. It is shown that there is always a linear combination of p+1 slices that gives a full-rank Toeplitz matrix. This derivation proves that consistent estimates can always be obtained with this set of p+1, 1-D slices. These results lead to the development of a new adaptive lattice algorithm with improved performance. Some results are presented comparing this scheme with previous algorithms based on a single slice. Estimation of the MA parameters of the obtained AR-compensated sequence completes the identification of the system. As this method is based on cumulants, the estimation will be unbiased, even in the presence of colored Gaussian noise
dc.format.extent4 p.
dc.subjectÀrees temàtiques de la UPC::Enginyeria electrònica
dc.subject.otherParameter estimation
dc.titleAdaptive system identification based on higher-order statistics
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorFonollosa, José A. R.; Masgrau, E.
local.citation.contributorIEEE International Conference on Acoustics, Speech, and Signal Processing
local.citation.pubplaceToronto, Ontario
local.citation.publicationNameInternational Conference on Acoustics, Speech and Signal Processing 1991

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