Results 131 to 140 of about 29,392 (243)

sBOSC: A Method for Source‐Level Identification of Neural Oscillations in Electromagnetic Brain Signals

Psychophysiology, Volume 63, Issue 6, June 2026.
ABSTRACT Neural oscillations are recognized as a fundamental component of brain electromagnetic activity. They are implicated in a wide range of cognitive processes and proposed as a core mechanism for brain communication. Nonetheless, detecting genuine neural oscillations remains a methodological challenge, particularly due to the difficulty of ...
Enrique Stern, Guiomar Niso, Almudena Capilla   +2 more
wiley   +1 more source

Detecting Turning Points with Many Predictors through Hidden Markov Models [PDF]

This paper explores the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series which offer reliable information to detect recessions in real time.
David Saint-Martin, Benoit Bellone
core  

Modelling human control behaviour with a Markov-chain switched bank of control laws [PDF]

, 1998
A probabilistic model of human control behaviour is described. It assumes that human behaviour can be represented by switching among a number of relatively simple behaviours.
Murray-Smith, R.
core  

Legume genome structures and histories inferred from Cercis canadensis and Chamaecrista fasciculata genomes

The Plant Journal, Volume 126, Issue 5, June 2026.
SUMMARY The legume family originated ca. 60–65 million years ago and soon diversified into at least six lineages (now extant subfamilies). The signal of whole genome duplications (WGD) is apparent in species sampled from all six subfamilies. The early diversification has posed difficulties for resolving the legume backbone structure and the timing of ...
Hyun‐oh Lee, Jacob S. Stai, Qiaoji Xu, Thulani Hewavithana, Pratheesh Soman, Rabnoor Batra, Alex Liu, Brandon D. Jordan, Rachel Walstead, Jerry Jenkins, Melissa Williams, Jenell Webber, Jane Grimwood, John T. Lovell, Tomáš Brůna, Shengqiang Shu, Keykhosrow Keymanesh, Joanne Eichenberger, Jeremy Schmutz, David M. Goodstein, Kerrie Barry, David Sankoff, Lingling Jin, James H. Leebens‐Mack, Steven B. Cannon   +24 more
wiley   +1 more source

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

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  

Estimating hidden semi-Markov chains from discrete sequences.

, 2003
International audienceThis article addresses the estimation of hidden semi-Markov chains from nonstationary discrete sequences. Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences.
Guédon, Yann
core   +1 more source

Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes

Geoscience Data Journal
Analysis of hydro‐climatological time series and spatiotemporal dynamics of meteorological variables has become critical in the context of climate change, especially in Southern African countries where rain‐fed agriculture is predominant.
Lovemore Chipindu, Walter Mupangwa, Isaiah Nyagumbo, Mainassara Zaman‐Allah   +3 more
doaj   +1 more source

Hidden Semi-Markov Models [PDF]

, 2018
openaire   +2 more sources

A hidden semi-Markov model for estimating burst suppression EEG. [PDF]

Annu Int Conf IEEE Eng Med Biol Soc, 2019
Chakravarty S, Baum TE, An J, Kahali P, Brown EN.   +4 more
europepmc   +1 more source

Using a continuous time hidden Markov process, with covariates, to model bed occupancy of people aged over 65 years

, 2001
Previously, the application of a continuous time hidden Markov model with discrete states was used to model geriatric inpatient behaviour. This was itself built on research using a discrete deterministic model to represent the flow of geriatric patients ...
Christodoulou, G., Taylor, G.J.
core   +1 more source