On rainfall seasonality using a hidden semi‐Markov model [PDF]
Journal of Geophysical Research: Atmospheres, 2007 A hidden semi‐Markov model (HSMM) has previously been used successfully to model breakpoint rainfall data which provide a continuous record of steady rainfall rates and the times of rain rate changes. These data contain more information than the commoner fixed period rain accumulation data.
J. Sansom, Peter C. Thomson
openalex +4 more sources
Decoding Chinese stock market returns: three-state hidden semi-Markov model [PDF]
, 2017 In this paper, we employ a three-state hidden semi-Markov model (HSMM) to explain the time-varying distribution of the Chinese stock market returns since 2005.
Liu, Zhenya, Wang, Shixuan
core +6 more sources
Segmenting Continuous Motions with Hidden Semi-markov Models and Gaussian Processes [PDF]
Frontiers in Neurorobotics, 2017 Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions.
Tomoaki Nakamura +5 more
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Applied Sciences, 2020 Heart sound segmentation (HSS) is a critical step in heart sound processing, where it improves the interpretability of heart sound disease classification algorithms.
Yibo Yin, Kainan Ma, Ming Liu
doaj +2 more sources
Seasonal movement behavior of domestic goats in response to environmental variability and time of day using Hidden Markov Models [PDF]
Movement EcologyBackground Current research on livestock movement ecology focuses on quantifying the factors that trigger alterations in movement behavior and understanding hidden mechanisms.
Hua Cheng +4 more
doaj +2 more sources
Structured Inference for Recurrent Hidden Semi-markov Model [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Segmentation and labeling for high dimensional time series is an important yet challenging task in a number of applications, such as behavior understanding and medical diagnosis. Recent advances to model the nonlinear dynamics in such time series data, has suggested to involve recurrent neural networks into Hidden Markov Models.
Bo Dai +5 more
openaire +2 more sources
A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment
Journal of Biomedical Informatics, 2018 In this paper, a Hidden Semi-Markov Model (HSMM) based approach is proposed to evaluate and monitor body motion during a rehabilitation training program. The approach extracts clinically relevant motion features from skeleton joint trajectories, acquired by the RGB-D camera, and provides a score for the subject's performance.
Capecci, Marianna +8 more
openaire +6 more sources
Unsupervised hidden semi-Markov model for automatic beat onset detection in 1D Doppler ultrasound. [PDF]
Physiol Meas, 2020 Objective: One dimensional (1D) Doppler ultrasound (DUS) is commonly used for fetal health assessment, during both regular prenatal visits and labor. It is used in preference to ECG and other modalities because of its simplicity and cost.
Katebi N +4 more
europepmc +2 more sources
Neonatal Bowel Sound Detection Using Convolutional Neural Network and Laplace Hidden Semi-Markov Model [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2021 Abdominal auscultation is a convenient, safe and inexpensive method to assess bowel conditions, which is essential in neonatal care. It helps early detection of neonatal bowel dysfunctions and allows timely intervention.
C. Sitaula +8 more
semanticscholar +1 more source
Hidden Markov Model of System Elements Technical Maintenance by Age [PDF]
E3S Web of Conferences, 2020 Technical maintenance is between the methods of operation reliability and effectiveness increasing for systems of different purposes including power systems.
Obzherin Yuriy +2 more
doaj +1 more source