Results 101 to 110 of about 8,821,946 (173)

Bayesian Estimation of Transition Rates in Two‐State Nonhomogeneous Markov Jump Processes With Intermittent Observations: An Honest‐Time Data‐Augmentation Approach

Scandinavian Journal of Statistics, Volume 53, Issue 3, Page 1343-1357, September 2026.
ABSTRACT A possibly time‐dependent transition intensity matrix or generator (Q(t))$$ \left(Q(t)\right) $$ characterizes the law of a Markov jump process (MP). For a time‐homogeneous MP, the transition probability matrix (TPM) can be expressed as a matrix exponential of Q$$ Q $$.
Dario Gasbarra, Sangita Kulathinal, Etienne Sebag   +2 more
wiley   +1 more source

A Novel Method for ECG-Free Heart Sound Segmentation in Patients with Severe Aortic Valve Disease

Sensors
Severe aortic valve diseases (AVD) cause changes in heart sounds, making phonocardiogram (PCG) analyses challenging. This study presents a novel method for segmenting heart sounds without relying on an electrocardiogram (ECG), specifically targeting ...
Elza Abdessater, Paniz Balali, Jimmy Pawlowski, Jérémy Rabineau, Cyril Tordeur, Vitalie Faoro, Philippe van de Borne, Amin Hossein   +7 more
doaj   +1 more source

Hidden Markov and Semi-Hidden Markov Models: an Application to Meteorological Data

openI dati meteorologici presentano una forte componente di variabilità e incertezza, rendendo complessa la loro analisi e la previsione. In questa tesi si indaga l'applicazione dei modelli Hidden Markov (HMM) e Semi-Hidden Markov (HSMM) all’analisi di ...
REMIGIO, FRANCESCA
core  

Multi-State Models for Panel Data: The msm Package for R [PDF]

Panel data are observations of a continuous-time process at arbitrary times, for example, visits to a hospital to diagnose disease status. Multi-state models for such data are generally based on the Markov assumption.
Christopher Jackson
core  

Anomaly Detection for Small Gas Pipeline Leaks Using an Acoustic Emission Sensor: A Semi-Supervised Approach via Ensemble Features and Gaussian Hidden Markov Model

IEEE Access
A method for detecting small leaks in gas pipelines based on semi-supervised learning is proposed. The proposed method models the time-varying behavior of signals collected from a flexible acoustic emission (AE) sensor that is attached to a gas pipe to ...
Byungjae Park, Hyejeong Ryu, Simaek Lee, Hyeongmin Yoo   +3 more
doaj   +1 more source

Bayesian nonparametric hidden Markov models with application to the analysis of copy-number-variation in mammalian genomes [PDF]

, 2009
We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models.
Yau, C., Papaspiliopoulos, Omiros, Roberts, Gareth O., Holmes, Christopher   +3 more
core  

Artificially intelligent accompaniment using Hidden Markov Models to model musical structure [PDF]

, 2008
Background in Music Performance and Accompaniment. Musical accompanists may not always be available during practice, or the available accompanist may not have the technical ability necessary.
Alan Smaill (16064372), Anna Jordanous (3195936), Jordanous, Anna, Smaill, Alan   +3 more
core  

Applied semi-Markov process

, 2005
Applied Semi-Markov Processes aims to give to the reader the tools necessary to apply semi-Markov processes in real-life problems. The book is self-contained and, starting from a low level of probability concepts, gradually brings the reader to a deep ...
Manca, Raimondo, Janssen, Jacques, JANSSEN J.   +2 more
core   +1 more source

Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model

IEEE Access
Power line communication (PLC) systems are essential for modern telecommunications, providing a cost-effective solution for data transmission over existing electrical wiring.
Akintunde Oluremi Iyiola, Theo G. Swart, Ayokunle Damilola Familua, Thokozani Shongwe   +3 more
doaj   +1 more source

Propositionalisation of multiple sequence alignments using probabilistic models [PDF]

, 2008
Multiple sequence alignments play a central role in Bioinformatics. Most alignment representations are designed to facilitate knowledge extraction by human experts.
Mutter, Stefan, Pfahringer, Bernhard, Holmes, Geoffrey   +2 more
core