Results 51 to 60 of about 101,818 (290)
Emotional Interactive Simulation System of English Speech Recognition in Virtual Context
Complexity, 2020 With the development of virtual scenes, the degree of simulation and functions of virtual reality have been very complete, providing a new platform and perspective for teaching design.
Dan Li
doaj +1 more source
Research on Lower Limb Step Speed Recognition Method Based on Electromyography
Micromachines, 2023 Wearable exoskeletons play an important role in people’s lives, such as helping stroke and amputation patients to carry out rehabilitation training and so on.
Peng Zhang, Pengcheng Wu, Wendong Wang
doaj +1 more source
Recursive smoothers for hidden discrete‐time Markov chains [PDF]
International Journal of Stochastic Analysis, 2005 We consider a discrete‐time Markov chain observed through another Markov chain. The proposed model extends models discussed by Elliott et al. (1995). We propose improved recursive formulae to update smoothed estimates of processes related to the model.
openaire +2 more sources
Business Strategy and the Environment, EarlyView.ABSTRACT The concept of predictive maintenance in advanced manufacturing systems is crucial from the point of view of resource efficiency in the era of high competitiveness forced by energy transformation in the digital economy. Against the backdrop of sustainability and the opportunities a data cooperative offers, the combination of predictive ...
Christian Schachtner +6 more
wiley +1 more source
IEEE Access, 2021 Medium- and long-term wind power output time series are required in stochastic programming model for power system planning. Hidden Markov model (HMM) is a common method to generate wind power output time series, which can simultaneously consider the ...
Yufei Li +6 more
doaj +1 more source
On Geometric Ergodicity of Skewed - SVCHARME models
, 2012 Markov Chain Monte Carlo is repeatedly used to analyze the properties of intractable distributions in a convenient way. In this paper we derive conditions for geometric ergodicity of a general class of nonparametric stochastic volatility models with ...
Asai +31 more
core +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Chemistry – A European Journal, EarlyView.Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source
Multi-Disjoint Path opportunistic networks with Hidden Markov Chain modeling
Alexandria Engineering JournalAdvancing the efficiency and reliability of wireless sensor networks is a paramount pursuit in modern networking research. In this context, we introduce a groundbreaking approach based on Hidden Markov Chain (HMC) modeling with opportunistic routing ...
Khurram Hussain +3 more
doaj +1 more source
Hidden fuzzy Markov chain model with K discrete classes [PDF]
, 2010 International audienceThis paper deals with a new unsupervised fuzzy Bayesian segmentation method based on the hidden Markov chain model, in order to separate continuous from discrete components in the hidden data.
Collet, Christophe +2 more
core +2 more sources
A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao +2 more
wiley +1 more source