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Mathematics of Control Signals and Systems
Article . 1999 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Data sources: zbMATH Open
DBLP
Article . 1999
Data sources: DBLP
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The Realization Problem for Hidden Markov Models

The realization problem for hidden Markov models
Authors: Anderson, Brian;

The Realization Problem for Hidden Markov Models

Abstract

Let \(X\) be a discrete-time finite-state Markov process and let \(Y=h(X,Z)\), where \(Z\) is some i.i.d. sequence, and where the output \(Y\) can take a finite number of values. This paper considers the realization question: given the probabilities of all finite-length output strings, under what circumstances and how can one construct an \(X\) as above and a mapping \(h\) as above such that for some \(Z\) as above \(Y=h(X,Z)\) generates finite-length output strings with the given probabilities. The theory presented in this paper is an extension of recent theoretical developments in the positive realization problem of linear system theory. This paper is clearly written and ends with a section ``conclusion'' that stimulates further research in this area.

Country
Australia
Related Organizations
Keywords

discrete-time finite-state Markov process, linear system theory, positive realization problem, hidden Markov models, Realizations from input-output data, Stochastic systems in control theory (general)

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Top 10%
Top 10%
Average
Green