Results 31 to 40 of about 6,150 (177)
SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS
Advanced Engineering Research, 2014 A hidden semi-Markov QP-model is considered; and the way it could be embedded in a general hidden semi-Markov model is shown. The estimation problem (the first of three classical theory problems of the hidden Markov models and hidden semi-Markov models ...
V. M. Deundyak, M. A. Zhdanova
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Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers [PDF]
Nonlinear Processes in Geophysics, 2011 Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms ...
M. Beyreuther, J. Wassermann
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Analysis and Comparison of Bitcoin and S and P 500 Market Features Using HMMs and HSMMs †
Information, 2019 We implement hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) on Bitcoin/US dollar (BTC/USD) with the aim of market phase detection. We make analogous comparisons to Standard and Poor’s 500 (S and P 500), a benchmark traditional ...
David Suda, Luke Spiteri
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An Analysis of Return States in Iran Stock Market: Hidden Semi-Markov Model Approach [PDF]
تحقیقات مالی, 2020 Objective: Analyzing the behavior of Tehran Stock Market, based on the daily asset return for the duration between 1387 and 1397 has been the main aim of this research.Methods: Tehran Stock Market daily asset return can be considered as a time-series and
Maysam Rafei, Mahin Shokri
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From Risk Assessment to Resilience Assessment. an Application to a Hazmat Storage Plant
Chemical Engineering Transactions, 2020 The purpose of this work is to outline a framework for assessing the resilience of a petrochemical storage plant, through the construction of a dynamic hierarchical Bayesian network. The BN approach allows keeping memory of the states, in order to manage
Tomaso Vairo +2 more
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Bayesian Nonparametric Hidden Semi-Markov Models
J. Mach. Learn. Res., 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode
Johnson, Matthew James, Willsky, Alan S.
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Sensors, 2022 From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from ...
Stefan Kalabakov +8 more
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A Spectral Algorithm for Inference in Hidden Semi-Markov Models
CoRR, 2014 Hidden semi-Markov models (HSMMs) are latent variable models which allow latent state persistence and can be viewed as a generalization of the popular hidden Markov models (HMMs). In this paper, we introduce a novel spectral algorithm to perform inference in HSMMs.
Igor Melnyk, Arindam Banerjee 0001
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A Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence [PDF]
Journal of Artificial Intelligence and Data Mining, 2017 This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference ...
V. Ghasemi, A. Pouyan, M. Sharifi
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Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi +1 more
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