Results 21 to 30 of about 241,122 (289)

Study on driver’s turning intention recognition hybrid model of GHMM and GGAP-RBF neural network

Advances in Mechanical Engineering, 2018
The accuracy and real time are crucial in turning intention recognition. Therefore, a hybrid model of Gaussian mixture hidden Markov and generalized growing and pruning algorithm for radial basis function neural network is constructed to recognize driver
Shu Wang, Qiang Yu, Xuan Zhao
doaj   +1 more source

Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions

Mathematics, 2022
This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step.
Arpad Gellert, Stefan-Alexandru Precup, Alexandru Matei, Bogdan-Constantin Pirvu, Constantin-Bala Zamfirescu   +4 more
doaj   +1 more source

Entropy rate calculations of algebraic measures

, 2011
Let $K = \{0,1,...,q-1\}$. We use a special class of translation invariant measures on $K^\mathbb{Z}$ called algebraic measures to study the entropy rate of a hidden Markov processes.
Marchand, Katy, Mulherkar, Jaideep, Nachtergaele, Bruno   +2 more
core   +1 more source

Dirichlet Process Hidden Markov Multiple Change-point Model [PDF]

, 2014
This paper proposes a new Bayesian multiple change-point model which is based on the hidden Markov approach. The Dirichlet process hidden Markov model does not require the specification of the number of change-points a priori.
Chong, Terence T. L., Ghosh, Pulak, Ko, Stanley I. M.   +2 more
core   +2 more sources

Convergence in distribution for filtering processes associated to Hidden Markov Models with densities

, 2013
Consider a filtering process associated to a hidden Markov model with densities for which both the state space and the observation space are complete, separable, metric spaces.
Kaijser, Thomas
core   +1 more source

fHMM: Hidden Markov Models for Financial Time Series in R

Journal of Statistical Software
Hidden Markov models constitute a versatile class of statistical models for time series that are driven by hidden states. In financial applications, the hidden states can often be linked to market regimes such as bearish and bullish markets or ...
Lennart Oelschläger, Timo Adam, Rouven Michels   +2 more
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Prediksi Kurs Rupiah Terhadap Dolar Dengan FTS-Markov Chain Dan Hidden Markov Model

Jurnal Derivat, 2019
Hidden Markov model is a development of the Markov chain where the state cannot be observed directly (hidden), but can only be observed, a set of other observations and combination of fuzzy logic and Markov chain to predict Rupiah exchange rate against ...
Maria Titah Jatipaningrum, Kris Suryowati, Libertania Maria Melania Esti Un   +2 more
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Error statistics of hidden Markov model and hidden Boltzmann model results

BMC Bioinformatics, 2009
Background Hidden Markov models and hidden Boltzmann models are employed in computational biology and a variety of other scientific fields for a variety of analyses of sequential data.
Newberg Lee A
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Hidden Markov Model Based on Logistic Regression

Mathematics, 2023
A hidden Markov model (HMM) is a useful tool for modeling dependent heterogeneous phenomena. It can be used to find factors that affect real-world events, even when those factors cannot be directly observed.
Byeongheon Lee, Joowon Park, Yongku Kim
doaj   +1 more source

Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks

International Journal of Advanced Robotic Systems, 2019
Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
doaj   +1 more source