Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
ARMA Spectral Estimation via Model Reduction
Department of Electrical Engineering, Linköping University. (Automatic Control)ORCID iD: 0000-0002-1927-1690
Department of Electrical Engineering, Linköping University.ORCID iD: 0000-0003-2298-6774
1986 (English)In: Proceedings of the 1986 American Control Conference, 1986, 1640-1641 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we study how to estimate autoregressive moving average (ARMA) processes via a high order autoregressive (AR) estimate and model reduction. The model reduction techniques considered are based on the L2-norm. internally balanced realizations, or the Hankelnorm. We apply this estimation technique to the problem of finding narrow-band signals in white noise.

Place, publisher, year, edition, pages
1986. 1640-1641 p.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-57968OAI: oai:DiVA.org:kth-57968DiVA: diva2:472776
Conference
1986 American Control Conference. Seattle, WA, USA
Note
QC 20120104Available from: 2012-01-04 Created: 2012-01-04 Last updated: 2013-09-05Bibliographically approved

Open Access in DiVA

No full text

Authority records BETA

Wahlberg, BoOttersten, Björn

Search in DiVA

By author/editor
Wahlberg, BoOttersten, Björn
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 29 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf