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Evaluating the CDMA System Using Hidden Markov and Semi Hidden Markov Models
2021
IPTEK: The Journal for Technology and Science
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A semi-hidden Markov model as a stochastic process is a modification of hidden Markov models with states that are no longer unobservable and less hidden. ...
Hidden Markov and Semi Hidden Markov models' applications have been investigated for evaluating the DS-CDMA link performance with different parameters. ...
The semi-hidden Markov model is a reliable stochastic model for modeling symbolic sequences with long runs and statistical inertia. ...
doi:10.12962/j20882033.v31i3.7016
fatcat:cqnapufa6rdo5fzlnyouzerz4q
An application of a semi-hidden Markov model in wireless communication systems
2019
Mathematical Sciences
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A semi-hidden Markov model as a type of stochastic processes is a modification of hidden Markov models with states that are no longer totally unobservable and are less hidden. ...
This mathematical model is employed for modeling data sequences with long runs, memory and statistical inertia. ...
All in all, the semi-hidden Markov model is a reliable stochastic model for modeling symbolic sequences with long runs and statistical inertia. ...
doi:10.1007/s40096-019-0279-3
fatcat:dpjils5fqracdccgbnbrjftdwy
An Optimized Multiple Semi-Hidden Markov Model for Credit Card Fraud Detection
2015
Indian Journal of Science and Technology
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The Multiple Semi-Hidden Markov Model is used for detecting fraudulent users and for optimizing training values Cuckoo Search algorithm is proposed. ...
The main intent of this research is automating the use of Multiple Semi-Hidden Markov Model, by liberating customers from the necessity of statistical knowledge. ...
To develop the usefulness of the Semi-Hidden Markov Model to assimilate the multiple observation of Semi-Hidden Markov Model which is named as Multiple Semi-Hidden Markov Model (MSHMM) 8 . ...
doi:10.17485/ijst/2015/v8i2/58081
fatcat:dpmig6o2yfb5jgyh23o36hz2hq
Hidden hybrid Markov/semi-Markov chains
2005
Computational Statistics & Data Analysis
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This type of model retains the flexibility of hidden semi-Markov chains for the modeling of short or medium size homogeneous zones along sequences but also enables the modeling of long zones with Markovian ...
This statistical modeling approach is illustrated by the analysis of branching and flowering patterns in plants. ...
Acknowledgments The author thanks Dominique Cellier for his helpful comments and Yves Caraglio for the botanical drawing. ...
doi:10.1016/j.csda.2004.05.033
fatcat:7hqrekchybd2dmrqgxke3sgrhq
Hidden semi-Markov model for anomaly detection
2008
Applied Mathematics and Computation
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Hidden semi-Markov model (HSMM) Maximum entropy principle (MEP) Segmental K-means algorithm a b s t r a c t In this paper, hidden semi-Markov model (HSMM) is introduced into intrusion detection. ...
be inappropriate for the modeling of audit data of computer systems. ...
Section 2 constructs a hidden semi-Markov model for normal behavior of computer system, and proposes an anomaly detection algorithm based on this model. ...
doi:10.1016/j.amc.2008.05.028
fatcat:2oijrpiv3jbjznjootafzdgp2y
Performance Comparison of Hmm Discrete Channel Modeling in Cdma Links
2010
International Journal of Computer Applications
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The performance comparison of two Markov models namely the Baum Welch Algorithm based HMM and Semi Hidden Markov Model has been evaluated for a DS-CDMA link in this work. ...
Validation includes a comparison of the run-length statistic for the original and regenerated error sequence from estimated models. ...
SIMULATION RESULTS The error sequence generated by the CDMA model is used to fit HMM model using two approaches: the BWA algorithm based HMM and the Semi-Hidden Markov model. ...
doi:10.5120/195-334
fatcat:lt5d5cjdefbnhbf6orn6nezyjq
hsmm — An R package for analyzing hidden semi-Markov models
2010
Computational Statistics & Data Analysis
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Hidden semi-Markov models are a generalization of the well-known hidden Markov model. ...
This package allows for the simulation and maximum likelihood estimation of hidden semi-Markov models. ...
Special thanks go to the main author of AMAPmod, Yann Guédon, who kindly provided us with estimation results from his package. Not to forget, we thank Gisela and Klaus Bulla for editorial assistance. ...
doi:10.1016/j.csda.2008.08.025
fatcat:2nb6en2zr5aaphbc227pbmqfeu
Multimodal analysis of speech prosody and upper body gestures using hidden semi-Markov models
2013
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
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In this work we investigate a new multimodal analysis framework to model relationships between intonational and gesture phrases using the hidden semi-Markov models (HSMMs). ...
We evaluate the multimodal analysis framework by generating speech prosody driven gesture animation, and employing both subjective and objective metrics. ...
In this study, we employ hidden semi-Markov model (HSMM) for multimodal analysis of gestures and prosody. ...
doi:10.1109/icassp.2013.6638339
dblp:conf/icassp/BozkurtAOYE13
fatcat:cklrs3rfzzb67fgx3lmhrimh44
Estimating Hidden Semi-Markov Chains From Discrete Sequences
2003
Journal of Computational And Graphical Statistics
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Hidden semi-Markov chains generalize hidden Markov chains and enable the modeling of various durational structures. ...
Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences. ...
We define hidden semi-Markov chains with absorbing states and thus define the likelihood of a state sequence generated by an underlying semi-Markov chain with a right censoring of the time spent in the ...
doi:10.1198/1061860032030
fatcat:edlnbui64zearaxxoqon6lqyy4
SEMI-SUPERVISED SEQUENCE CLASSIFICATION WITH HMMs
2005
International journal of pattern recognition and artificial intelligence
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This paper applies semi-supervised classification algorithms, based on hidden Markov models, to classify sequences. ...
For model-based classification, semi-supervised learning amounts to using both labeled and unlabeled data to train model parameters. ...
., different number of hidden states for hidden Markov models) on the performance of semi-supervised learning. ...
doi:10.1142/s0218001405004034
fatcat:zl6gee7l7feo5hsbtl3ipluf4i
INTEGRATING MARKOV CHAIN MODELS AND L-SYSTEMS TO SIMULATE THE ARCHITECTURAL DEVELOPMENT OF APPLE TREES
2006
Acta Horticulturae
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The approach is based on using an L-systems framework to integrate a Markov model of terminal bud fate and a number of hidden semi-Markov models of axial bud fate. ...
An approach for modelling and simulating the architectural development of apple trees is presented. ...
Hidden Semi-Markov Models The hidden semi-Markov modelling of the branching along GUs revealed the presence of distinct zones. General patterns could be observed in the hidden semi-Markov models. ...
doi:10.17660/actahortic.2006.707.7
fatcat:66pr3waefvcdbc7jiojwgkw6mm
Markov and Semi-Markov Switching Linear Mixed Models Used to Identify Forest Tree Growth Components
2009
Biometrics
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In this paper we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. ...
The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) while the linear mixed models attached to each state of the underlying semi-Markov chain ...
Analysis of the plant 5 architecture via tree-structured statistical models: The hidden Markov tree models. New 6 Phytologist 166, 813-825. 7 Ephraim, Y. and Merhav, N. (2002). ...
doi:10.1111/j.1541-0420.2009.01338.x
pmid:19912173
fatcat:6fhzezgwvffuxdkrhygmcytsuu
Time-dependent Interactive Graphical Models for Human Activity Analysis
[chapter]
2007
Advances in Pattern Recognition
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The proposed model, called Coupled Hidden Duration Semi Markov Model, takes inspiration from the large literature on Hidden Markov Models and its variants. ...
The novelty introduced by the model is the capability of dealing with interacting state processes, where 1) states that characterize a single process exhibit different time durations, and 2) different ...
Coupled Hidden Duration Semi Markov Model As pointed out in (Murphy 2002) , Semi Markov processes can be approached as Markov processes whose generalized states (simply pointed out as states in this paper ...
doi:10.1007/978-1-84628-945-3_11
fatcat:aaj2rbeanffppgzguhvnjx4bxm
Detecting anomalous events at railway level crossings
2013
Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit
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In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full Two Dimensional Hidden Markov Model and Spatial Hidden Markov Model to model the normal activities of people. ...
The proposed approaches are evaluated using the publicly available UCSD datasets and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. ...
ACKNOWLEDGEMENT The authors are grateful to the CRC for Rail Innovation (established and supported under the Australian Government's Cooperative Research Centres program) for the funding of this research ...
doi:10.1177/0954409713501296
fatcat:uv3zyi3c4zdf7hxhwasji2f2kq
Hidden Semi Markov Models for Multiple Observation Sequences: ThemhsmmPackage forR
2011
Journal of Statistical Software
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This paper describes the R package mhsmm which implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. ...
Hidden Markov models only allow a geometrically distributed sojourn time in a given state, while hidden semi-Markov models extend this by allowing an arbitrary sojourn distribution. ...
Acknowledgments This study was part of the BIOSENS project funded by the Danish Ministry of Food, Agriculture and Fisheries and the Danish Cattle Industry via Finance Committee Cattle. ...
doi:10.18637/jss.v039.i04
fatcat:7bvdwpwcgvdl7b3oei6ruk7ykq
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