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

Augusto Ferrante, Chiara Masiero, Michele Pavon

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

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.

Original languageEnglish (US)
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1479-1484
Number of pages6
ISBN (Print)9781612848006
DOIs
StatePublished - 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Country/TerritoryUnited States
CityOrlando, FL
Period12/12/1112/15/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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