@inproceedings{b7d9b1765eb740bf93804e17e4b84e6e,
title = "Consistent HMM parameter estimation using Kerridge inaccuracy rates",
abstract = "In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on Kerridge inaccuracy rate (KIR) concepts. Under mild identifiability conditions, we prove that our online KIR-based estimator is strongly consistent. In simulation studies, we illustrate the convergence behaviour of our proposed online KIR-based estimator and provide a counter-example illustrating the local convergence properties of the well known recursive maximum likelihood estimator (arguably the best existing solution).",
author = "Molloy, \{Timothy L.\} and Ford, \{Jason J.\}",
year = "2013",
doi = "10.1109/AUCC.2013.6697250",
language = "English",
isbn = "9781479924981",
series = "2013 3rd Australian Control Conference, AUCC 2013",
pages = "73--78",
booktitle = "2013 3rd Australian Control Conference, AUCC 2013",
note = "2013 3rd Australian Control Conference, AUCC 2013 ; Conference date: 04-11-2013 Through 05-11-2013",
}