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De novo atomic protein structure modeling for cryoEM density maps using 3D transformer and HMM
Accurately building 3D atomic structures from cryo-EM density maps is a crucial step in cryo-EM-based protein structure determination. Converting...
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Asynchronous fault detection for hidden Markov jump systems with dynamic event-triggered mechanism
In the present paper, the problem of asynchronous fault detection (FD) for Markov jump system based on a dynamic event-triggered transmission...
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Hidden Markov models for longitudinal rating data with dynamic response styles
This work deals with the analysis of longitudinal ordinal responses. The novelty of the proposed approach is in modeling simultaneously the temporal...
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The Prediction of Remaining Useful Life of Aluminum Reduction Cells Based on Improved Hidden Semi-Markov Model
An improved prediction algorithm of the hidden semi-markov model (HSMM) is proposed to predict the remaining useful life (RUL) of aluminum reduction...
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Not all bull and bear markets are alike: insights from a five-state hidden semi-Markov model
This paper employs the hidden semi-Markov model and a novel model selection procedure to determine different regimes in the US stock market. The...
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Highway Lane-Changing Prediction Using a Hierarchical Software Architecture based on Support Vector Machine and Continuous Hidden Markov Model
Lane changing behavior is one of the most essential and complex driving attributes. The lack of proper lane changing behavior can lead to collisions...
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Bayesian Hidden Markov Models for Early Warning
We show how Bayesian hidden Markov models may be employed to build early warning systems of particular risky events. The adopted model formulation...
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Hidden Markov Models with Unobservable Transitions
We consider Hidden Markov Models (HMMs) that admit unobservable \(\varepsilon \)...
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Integrated Tuning of Hidden Markov Parametric Optimization Model with Genetic Algorithm for Electricity Market Forecasting
This paper presents Hidden Markov Parametric Optimization Model (HMPOM) integrated and tuned with Genetic Algorithm (GA) for Electricity Market...
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Univariate Hidden Markov Models
In this chapter we discuss a number of examples of hidden Markov models applied to univariate time series. We first present a basic Gaussian hidden...
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Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model
BackgroundPredicting the response of cancer cell lines to specific drugs is an essential problem in personalized medicine. Since drug response is...
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Applying Hidden Markov Modelling to Fine-Scale Telemetry
Recent developments in fine-scale acoustic telemetry have resulted in large datasets containing highly detailed information on fish movement. A...
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Multivariate Hidden Markov Models
This chapter provides three extended example analyses, applying hidden Markov models to multivariate time series. The first example (Sect. 6.1)...
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On robust estimation of hidden semi-Markov regime-switching models
Regime-switching models provide an efficient framework for capturing the dynamic behavior of data observed over time and are widely used in economic...
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An Innovative Method for Speech Signal Emotion Recognition Based on Spectral Features Using GMM and HMM Techniques
Speech is one of the communication processes of humans. One of the important features of speech is to convey the inner feelings of the person to the...
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Inhomogeneous hidden semi-Markov models for incompletely observed point processes
A general class of inhomogeneous hidden semi-Markov models (IHSMMs) is proposed for modelling partially observed processes that do not necessarily...
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hhsmm: an
R package for hidden hybrid Markov/semi-Markov modelsThis paper introduces the hhsmm
R package, which involves functions for initializing, fitting, and predication of hidden hybrid Markov/semi-Markov...
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Matrix-Variate Hidden Markov Regression Models: Fixed and Random Covariates
Two families of matrix-variate hidden Markov regression models (MV-HMRMs) are here introduced. The distinction between them relies on the role of the...
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An Efficient Sign Language Recognition (SLR) System Using Camshift Tracker and Hidden Markov Model (HMM)
An efficient Sign Language Recognition (SLR) system could facilitate communication with hearing impaired persons by identifying the sign gestures....
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Evaluation of vicinity-based hidden Markov models for genotype imputation
BackgroundThe decreasing cost of DNA sequencing has led to a great increase in our knowledge about genetic variation. While population-scale projects...
