A hidden semi-Markov model for estimating burst suppression EEG. [PDF]
Annu Int Conf IEEE Eng Med Biol Soc, 2019 Burst suppression is an electroencephalogram (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. This pattern is distinguished by short-duration band-limited electrical activity (bursts) interspersed between relatively near-isoelectric periods (suppressions).
Chakravarty S +4 more
europepmc +8 more sources
Hidden Semi-Markov Models-Based Visual Perceptual State Recognition for Pilots [PDF]
Sensors, 2023 Pilots’ loss of situational awareness is one of the human factors affecting aviation safety. Numerous studies have shown that pilot perception errors are one of the main reasons for a lack of situational awareness without a proper system to detect these ...
Lina Gao, Changyuan Wang, Gongpu Wu
doaj +2 more sources
Bayesian Nonparametric Hidden Semi-Markov Models [PDF]
Journal of Machine Learning Research, 2022 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
Matthew Johnson, Alan S. Willsky
openalex +4 more sources
biomvRhsmm: genomic segmentation with hidden semi-Markov model. [PDF]
Biomed Res Int, 2014 High-throughput technologies like tiling array and next-generation sequencing (NGS) generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification), regions of deletion and amplification (copy number variation), or regions characterized by particular ...
Du Y, Murani E, Ponsuksili S, Wimmers K.
europepmc +6 more sources
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
doaj +2 more sources
Implementation of hidden semi-Markov models
, 2020 One of the most frequently used concepts applied to a variety of engineering and scientific studies over the recent years is that of a Hidden Markov Model (HMM). The Hidden semi-Markov model (HsMM) is contrived in such a way that it does not make any premise of constant or geometric distributions of a state duration.
Nagendra Abhinav Dasu
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A New State Recognition and Prognosis Method Based on a Sparse Representation Feature and the Hidden Semi-Markov Model [PDF]
IEEE Access, 2020 Equipment degradation state recognition and prognosis are considered two significant parts of a prognostics and health management (PHM) system that help to reduce downtime and decrease economic losses.
Yun-Fei Ma +5 more
doaj +2 more sources
The Hierarchical Dirichlet Process Hidden Semi-Markov Model [PDF]
, 2010 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM.
Johnson, Matthew James, Willsky, Alan S
core +4 more sources
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
IEEE Access, 2016 In this paper, a joint feature selection and parameter estimation algorithm is presented for hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs).
Stephen Adams +2 more
doaj +3 more sources
Evolving Connectionist System and Hidden Semi-Markov Model for Learning-Based Tool Wear Monitoring and Remaining Useful Life Prediction [PDF]
IEEE Access, 2022 Tool wear can cause dimensional accuracy and poor surface quality in milling process. During the operation of tool wear, it can also cause breakage and damage of the workpieces.
Muquan Lin +3 more
doaj +2 more sources