Results 41 to 50 of about 14,908,682 (295)

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
doaj   +1 more source

Perfect posterior simulation for mixture and hidden Markov models [PDF]

, 2010
In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models.
Berthelsen, Kasper Klitgaard, Laird A. Breyer, Berthelsen, Kasper K., Kasper K. Berthelsen, Roberts, Gareth O., Breyer, Laird A., Gareth O. Roberts   +6 more
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
doaj   +1 more source

Application of Poisson Hidden Markov Model to Predict Number of PM2.5 Exceedance Days in Tehran During 2016-2017 [PDF]

Avicenna Journal of Environmental Health Engineering, 2017
PM2.5 is an important indicator of air pollution. This pollutant can result in lung and respiratory problems in people. The aim of the present study was to predict number of PM2.5 exceedance days using Hidden Markov Model considering Poisson distribution
Fatemeh Sarvi, Azam Nadali, Mahmoud Khodadost, Melika Kharghani Moghaddam, Majid Sadeghifar   +4 more
doaj   +1 more source

Scoring hidden Markov models [PDF]

Bioinformatics, 1997
Statistical sequence comparison techniques, such as hidden Markov models and generalized profiles, calculate the probability that a sequence was generated by a given model. Log-odds scoring is a means of evaluating this probability by comparing it to a null hypothesis, usually a simpler statistical model intended to represent the universe of sequences ...
Christian Barrett, Richard Hughey, Kevin Karplus   +2 more
openaire   +3 more sources

A statistical multiresolution approach for face recognition using structural hidden Markov models [PDF]

, 2007
This paper introduces a novel methodology that combines the multiresolution feature of the discrete wavelet transform (DWT) with the local interactions of the facial structures expressed through the structural hidden Markov model (SHMM).
A. Amira, P Nicholl, D. Bouchaffra, Perrott, R H, P. Nicholl, R H Perrott, Perrott, RH, D Bouchaffra, Nicholl, P, Amira, A, Bouchaffra, D, A Amira, R. H. Perrott   +12 more
core   +1 more source

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
doaj   +1 more source

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

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Robot introspection through learned hidden Markov models [PDF]

, 2006
In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability.
Maria Fox, Malik Ghallab, Ghallab, M., Long, D., Fox, M., Guillaume Infantes, Infantes, G., Derek Long   +7 more
core   +2 more sources