NDLI: A new metric for multivariate spectral estimation leading to lowest complexity spectra

Content Provider	IEEE Xplore Digital Library
Author	Ferrante, A. Masiero, C. Pavon, M.
Copyright Year	2011
Description	Author affiliation: Dipartimento di Ingegneria dell'Informazione, Università di Padova, via Gradenigo 6/B, 35131, Italy (Ferrante, A.; Masiero, C.) \|\| Dipartimento di Matematica Pura ed Applicata, Università di Padova, via Trieste 63, 35131, Italy (Pavon, M.)
Abstract	A new multivariate spectral estimation technique is proposed. It is based on a constrained spectrum approximation problem, where the distance between spectra is derived from the relative entropy rate between stationary Gaussian processes. This approach may be viewed as an extension of the high-resolution estimator called THREE introduced by Byrnes, Georgiou and Lindquist in 2000. The corresponding solution features a complexity upper bound which is equal to the one featured by THREE in the scalar case thereby improving on the one so far available in the multichannel framework. The solution is computed by means of a globally convergent, matricial Newton-type algorithm. Comparative simulation indicates that this new technique outperforms PEM and N4SID in the case of short data records.
Starting Page	1479
Ending Page	1484
File Size	196927
Page Count	6
File Format	PDF
ISBN	9781612848006
ISSN	07431546
e-ISBN	9781612848013
e-ISBN	9781612847993
DOI	10.1109/CDC.2011.6160890
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Entropy Complexity theory Upper bound Covariance matrix Indexes Convergence
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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