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
Fast, non-iterative estimation of Hidden Markov models
KTH, Superseded Departments, Signals, Sensors and Systems. (Signalbehandling, Signal Processing)ORCID iD: 0000-0002-9368-3079
University of Newcastle.
1998 (English)In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Seattler, WA, USA, 1998, Vol. 4, no Piscataway, NJ, United States, 2253-2256 p.Conference paper, Published paper (Refereed)
Abstract [en]

The solution of many important signal processing problems depends on the estimation of the parameters of a Hidden Markov Model (HMM). Unfortunately, to date the only known methods for performing this estimation have been iterative, and therefore computationally demanding. By way of contrast, this paper presents a new fast and non-iterative method that utilizes certain recent 'state spaced subspace system identification' (4SID) ideas from the control theory literature. A short simulation example presented here indicates this new technique to be almost as accurate as Maximum-Likelihood estimation, but an order of magnitude less computationally demanding than the Baum-Welch (EM) algorithm.

Place, publisher, year, edition, pages
Seattler, WA, USA, 1998. Vol. 4, no Piscataway, NJ, United States, 2253-2256 p.
Series
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. Part 1 (of 6)
Keyword [en]
Algorithms, Computer simulation, Identification (control systems), Markov processes, Mathematical models, Parameter estimation, Probability, Problem solving, Baum-Welch algorithm, Hidden Markov model, State spaced subspace system identification, Signal processing
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-60583DOI: 10.1109/ICASSP.1998.681597OAI: oai:DiVA.org:kth-60583DiVA: diva2:479515
Note
NR 20140805Available from: 2012-01-17 Created: 2012-01-13 Last updated: 2012-01-17Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Hjalmarsson, Håkan

Search in DiVA

By author/editor
Hjalmarsson, Håkan
By organisation
Signals, Sensors and Systems
Control EngineeringSignal Processing

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 27 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