The ‘aukward’ use of hidden Markov models in a pursuit-diving seabird: semi-supervised HMMs improve behavioural classification and energetic inference in auks [PDF]
Movement EcologyGlobal seabird declines underline the need for accurate behavioural inference at sea to guide conservation. For pursuit-diving species such as auks, differentiating between resting and foraging is difficult due to similar above-water movement patterns ...
Astrid Dedieu +4 more
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Combining EEG signals from the 2 members of a team to improve event identification [PDF]
NeuroImage: ReportsWe examined the potential of combining EEG signals from multiple individuals to identify critical events in a team task. In this study two subjects played a video game in which they had complementary roles, one player serving as a Bait to distract 5 ...
Jon M. Fincham +2 more
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Bayesian Nonparametric Hidden Semi-Markov Models
J. Mach. Learn. Res., 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode
Johnson, Matthew James, Willsky, Alan S.
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Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. [PDF]
Neuroimage, 2019 Shappell H +3 more
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Deep Hidden Semi-Markov Model-Based Speech Synthesis
IEEE AccessThis paper proposes a speech synthesis technique based on a neural sequence-to-sequence (Seq2Seq) model that incorporates the structure of hidden semi-Markov models (HSMMs).
Yoshihiko Nankaku +6 more
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Hidden Semi-Markov Models for Predictive Maintenance [PDF]
Mathematical Problems in Engineering, 2015 Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we
Francesco Cartella +3 more
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Unsupervised Classification of Human Activity with Hidden Semi-Markov Models
Applied System Innovation, 2022 The modern sedentary lifestyle is negatively influencing human health, and the current guidelines recommend at least 150 min of moderate activity per week. However, the challenge is how to measure human activity in a practical way.
Francesca Romana Cavallo +2 more
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Prediction of PM2.5 pollution in Tehran air based on temperature and pressure using Markovian regime-switching non-parametric additive transitive regression model [PDF]
ریاضی و جامعه, 2023 In this paper, we introduce the Markovian regime-switching regression model, which is a graphical model based on the hidden Markov model. This model can be viewed as a clustered regression model, in which a Markov process models the transition from one ...
Morteza Amini
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Heavy tailed hidden semi-markov models [PDF]
Communications in Statistics. Stochastic Models, 1998 Summary: Hidden semi-Markov models have been proposed by \textit{K. S. Meier-Hellstern}, \textit{P. E. Wirth}, \textit{Y. L. Yan} and \textit{D. A. Hoeflin} [in: Teletraffic and datatraffic in a period of change (A. Jensen and V. B. Iversen (eds.)), 167-192 (1991)] to model the times between transmission of packets at a source.
Resnick, Sidney, Subramanian, Ajay
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Human Activities Recognition using Semi-Supervised SVM and Hidden Markov Models
TecnoLógicas, 2022 Automatic human activity recognition is an area of interest for developing health, security, and sports applications. Currently, it is necessary to develop methods that facilitate the training process and reduce the costs of this process.
Santiago Morales García +2 more
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