Asymptotic smoothing errors for hidden markov models

Louis Shue; Brian D.O. Anderson; Franky De Bruyne

doi:10.1109/78.886992

Asymptotic smoothing errors for hidden markov models

Louis Shue, Brian D.O. Anderson, Franky De Bruyne

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

In this paper, the asymptotic smoothing error for hidden Markov models (HMMs) is investigated using hypothesis testing ideas. A family of HMMs is studied parametrised by a positive constant e, which is a measure of the frequency of change. Thus, when e -> 0, the HMM becomes increasingly slower moving. We show that the smoothing error is O(e). These theoretical predictions are confirmed by a series of simulations.

Original language	English
Pages (from-to)	3289-3302
Number of pages	14
Journal	IEEE Transactions on Signal Processing
Volume	48
Issue number	12
DOIs	https://doi.org/10.1109/78.886992
Publication status	Published - 2000

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10.1109/78.886992

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title = "Asymptotic smoothing errors for hidden markov models",

abstract = "In this paper, the asymptotic smoothing error for hidden Markov models (HMMs) is investigated using hypothesis testing ideas. A family of HMMs is studied parametrised by a positive constant e, which is a measure of the frequency of change. Thus, when e -> 0, the HMM becomes increasingly slower moving. We show that the smoothing error is O(e). These theoretical predictions are confirmed by a series of simulations.",

keywords = "Asymptotic error, Hidden markov model, Smoothing",

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AU - Shue, Louis

AU - Anderson, Brian D.O.

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AB - In this paper, the asymptotic smoothing error for hidden Markov models (HMMs) is investigated using hypothesis testing ideas. A family of HMMs is studied parametrised by a positive constant e, which is a measure of the frequency of change. Thus, when e -> 0, the HMM becomes increasingly slower moving. We show that the smoothing error is O(e). These theoretical predictions are confirmed by a series of simulations.

KW - Asymptotic error

KW - Hidden markov model

KW - Smoothing

UR - https://www.scopus.com/pages/publications/0034429493

U2 - 10.1109/78.886992

DO - 10.1109/78.886992

M3 - Article

SN - 1053-587X

VL - 48

SP - 3289

EP - 3302

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 12

ER -

Asymptotic smoothing errors for hidden markov models

Abstract

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