Results 11 to 20 of about 22,587 (196)
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
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Fatigue crack fault diagnosis and prognosis based on hidden semi-Markov model
The Journal of Engineering, 2018 Aiming at the fault diagnosis and remaining useful life (RUL) prediction of fatigue cracks of a helicopter main gearbox planet carrier, this article proposes a hidden semi-Markov model (HSMM) methodology, which introduces the explicit state durational ...
Lei Fan +3 more
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Journal of Electrical Systems and Information Technology, 2017 This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM) Toolkit (HTK) without explicit segmentation. The first phase is preprocessing, where the data is introduced
El Moubtahij Hicham +2 more
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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
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Bernoulli Filters for Multiple Correlated Sensors
IEEE Access, 2021 The Bernoulli filter is a general, Bayes-optimal solution for tracking a single disappearing and reappearing target, using a single sensor whose observations are corrupted by missed detections and a general, known clutter process.
Ronald Mahler
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Hidden Markov model speed heuristic and iterative HMM search procedure [PDF]
BMC Bioinformatics, 2010 Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require considerable time to search large sequence databases.We have designed a series of database filtering steps, HMMERHEAD, that are applied prior to the scoring algorithms, as implemented in the
L. Steven Johnson +2 more
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Enhanced Map-Matching Algorithm with a Hidden Markov Model for Mobile Phone Positioning
ISPRS International Journal of Geo-Information, 2017 Numerous map-matching techniques have been developed to improve positioning, using Global Positioning System (GPS) data and other sensors. However, most existing map-matching algorithms process GPS data with high sampling rates, to achieve a higher ...
An Luo, Shenghua Chen, Bin Xv
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Sequence Classification Method Based on Neighborhood Information in Unconstrained Space [PDF]
Jisuanji gongcheng, 2016 A sequence classification methodology is proposed based on a conjecture that neighborhood’s similarity results in sequence’s similarity.The constrained Hidden Markov Model(HMM) space defined by sample is transformed to unconstrained HMM space.The ...
WANG Xingfu,WANG Yuqi
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Arabic Dialects System using Hidden Markov Models (HMMs)
WSEAS TRANSACTIONS ON COMPUTERS, 2022 The Arabic language has many different dialects and it must be recognized before using the automatic speech recognition (ASR). On the other hand, it is observed in all Arab countries that the standard Arabic language is widely written and used in an official speech, newspapers, public administration, and schools but it is not used in daily ...
Zakaria Suliman Zubi, Eman Jibril Idris
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Hierarchically Clustered HMM for Protein Sequence Motif Extraction with Variable Length
Tsinghua Science and Technology, 2014 Protein sequence motifs extraction is an important field of bioinformatics since its relevance to the structural analysis. Two major problems are related to this field: (1) searching the motifs within the same protein family; and (2) assuming a window ...
Cody Hudson, Bernard Chen, Dongsheng Che
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