Results 11 to 20 of about 8,159 (239)
SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS
Advanced Engineering Research, 2014 A hidden semi-Markov QP-model is considered; and the way it could be embedded in a general hidden semi-Markov model is shown. The estimation problem (the first of three classical theory problems of the hidden Markov models and hidden semi-Markov models ...
V. M. Deundyak, M. A. Zhdanova
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Evaluating the CDMA System Using Hidden Markov and Semi Hidden Markov Models
IPTEK The Journal for Technology and Science, 2021 CDMA is an important and basic part of today’s communications technologies. This technology can be analyzed efficiently by reducing the time, computation burden, and cost by characterizing the physical layer with a Markov Model. Waveform level simulation is generally used for simulating different parts of a digital communication system.
Shirin Kordnoori +3 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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hsmm — An R package for analyzing hidden semi-Markov models
Computational Statistics & Data Analysis, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bulla, Jan, Bulla, Ingo, Nenadic, Oleg
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Early Life Stress Affects Human Decision Making by Increasing Expectations of Volatility. [PDF]
Dev SciABSTRACT People learn most effectively when they can flexibly modify strategies to accommodate environmental changes. Here, we explore how chronic early life stress influences the ways individuals weight and prioritize new information when making decisions. To do so, we examined the choices of 11–16‐year‐old children in a reward learning task. Children
Smith KE +4 more
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Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 Hidden Markov model (HMM) has been a popular choice for financial time series modeling due to its advantage in capturing dynamic regimes. However, HMM's implicit assumption that the state duration follows a geometric distribution is too strong to hold in
Zekun Xu, Ye Liu
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Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi +1 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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Hidden Markov models: the best models for forager movements? [PDF]
PLoS ONE, 2013 One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs).
Rocio Joo +3 more
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An Analysis of Return States in Iran Stock Market: Hidden Semi-Markov Model Approach [PDF]
تحقیقات مالی, 2020 Objective: Analyzing the behavior of Tehran Stock Market, based on the daily asset return for the duration between 1387 and 1397 has been the main aim of this research.Methods: Tehran Stock Market daily asset return can be considered as a time-series and
Maysam Rafei, Mahin Shokri
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