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
How to monitor and mitigate stair-casing in L1 trend filtering
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-0355-2663
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-1927-1690
2015 (English)In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, IEEE conference proceedings, 2015, 3946-3950 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

In this paper we study the estimation of changing trends in time-series using ℓ1 trend filtering. This method generalizes 1D Total Variation (TV) denoising for detection of step changes in means to detecting changes in trends, and it relies on a convex optimization problem for which there are very efficient numerical algorithms. It is known that TV denoising suffers from the so-called stair-case effect, which leads to detecting false change points. The objective of this paper is to show that ℓ1 trend filtering also suffers from a certain stair-case problem. The analysis is based on an interpretation of the dual variables of the optimization problem in the method as integrated random walk. We discuss consistency conditions for ℓ1 trend filtering, how to monitor their fulfillment, and how to modify the algorithm to avoid the stair-case false detection problem.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 3946-3950 p.
Keyword [en]
change point detection, Fused Lasso, generalized lasso, TV denoising, ℓ1 trend filtering
National Category
Control Engineering Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-181499DOI: 10.1109/ICASSP.2015.7178711Scopus ID: 2-s2.0-84946025714ISBN: 9781467369978 (print)OAI: oai:DiVA.org:kth-181499DiVA: diva2:912308
Conference
40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015, 19 April 2014 through 24 April 2014
Note

QC 20160316

Available from: 2016-03-16 Created: 2016-02-02 Last updated: 2016-03-16Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Rojas, CristianWahlberg, Bo
By organisation
Automatic ControlACCESS Linnaeus Centre
Control EngineeringComputational Mathematics

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 7 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