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Introduction to Hidden Semi-Markov Models

Introduction to Hidden Semi-Markov Models
A Book

by John Van der Hoek,Robert J. Elliott

  • Publisher : Cambridge University Press
  • Release : 2019
  • Pages : 329
  • ISBN : 1108421601
  • Language : En, Es, Fr & De
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Develops the theory of Markov and semi-Markov processes in an elementary setting suitable for senior undergraduate and graduate students.

Semi-Markov Chains and Hidden Semi-Markov Models toward Applications

Semi-Markov Chains and Hidden Semi-Markov Models toward Applications
Their Use in Reliability and DNA Analysis

by Vlad Stefan Barbu,Nikolaos Limnios

  • Publisher : Springer Science & Business Media
  • Release : 2009-01-07
  • Pages : 226
  • ISBN : 0387731733
  • Language : En, Es, Fr & De
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Here is a work that adds much to the sum of our knowledge in a key area of science today. It is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. A unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis. The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers.

Hidden Semi-Markov Models

Hidden Semi-Markov Models
Theory, Algorithms and Applications

by Shun-Zheng Yu

  • Publisher : Morgan Kaufmann
  • Release : 2015-10-22
  • Pages : 208
  • ISBN : 0128027711
  • Language : En, Es, Fr & De
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Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. Hidden Semi-Markov Models: Theory, Algorithms and Applications provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science. Discusses the latest developments and emerging topics in the field of HSMMs Includes a description of applications in various areas including, Human Activity Recognition, Handwriting Recognition, Network Traffic Characterization and Anomaly Detection, and Functional MRI Brain Mapping. Shows how to master the basic techniques needed for using HSMMs and how to apply them.

Hidden Semi-Markov Models for Predictive Maintenance of Rotating Elements

Hidden Semi-Markov Models for Predictive Maintenance of Rotating Elements
A Book

by Christoph Anger

  • Publisher : Unknown Publisher
  • Release : 2018
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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A Multivariate Hidden Semi-Markov Model of Customer-multichannel Engagement

A Multivariate Hidden Semi-Markov Model of Customer-multichannel Engagement
A Book

by Sharmistha Sikdar,Giles Hooker

  • Publisher : Unknown Publisher
  • Release : 2019
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Semi-Markov Models

Semi-Markov Models
Theory and Applications

by Jacques Janssen

  • Publisher : Springer Science & Business Media
  • Release : 2013-11-11
  • Pages : 588
  • ISBN : 148990574X
  • Language : En, Es, Fr & De
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This book is the result of the International Symposium on Semi Markov Processes and their Applications held on June 4-7, 1984 at the Universite Libre de Bruxelles with the help of the FNRS (Fonds National de la Recherche Scientifique, Belgium), the Ministere de l'Education Nationale (Belgium) and the Bernoulli Society for Mathe matical Statistics and Probability. This international meeting was planned to make a state of the art for the area of semi-Markov theory and its applications, to bring together researchers in this field and to create a platform for open and thorough discussion. Main themes of the Symposium are the first ten sections of this book. The last section presented here gives an exhaustive biblio graphy on semi-Markov processes for the last ten years. Papers selected for this book are all invited papers and in addition some contributed papers retained after strong refereeing. Sections are I. Markov additive processes and regenerative systems II. Semi-Markov decision processes III. Algorithmic and computer-oriented approach IV. Semi-Markov models in economy and insurance V. Semi-Markov processes and reliability theory VI. Simulation and statistics for semi-Markov processes VII. Semi-Markov processes and queueing theory VIII. Branching IX. Applications in medicine X. Applications in other fields v PREFACE XI. A second bibliography on semi-Markov processes It is interesting to quote that sections IV to X represent a good sample of the main applications of semi-Markov processes i. e.

Research Review

Research Review
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1985
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Hidden Markov Models for Time Series

Hidden Markov Models for Time Series
An Introduction Using R, Second Edition

by Walter Zucchini,Iain L. MacDonald,Roland Langrock

  • Publisher : CRC Press
  • Release : 2017-12-19
  • Pages : 370
  • ISBN : 1482253844
  • Language : En, Es, Fr & De
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data

Earthquake Statistical Analysis through Multi-state Modeling

Earthquake Statistical Analysis through Multi-state Modeling
A Book

by Irene Votsi,Nikolaos Limnios,Eleftheria Papadimitriou,Georgios Tsaklidis

  • Publisher : John Wiley & Sons
  • Release : 2019-04-02
  • Pages : 180
  • ISBN : 1786301504
  • Language : En, Es, Fr & De
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Earthquake occurrence modeling is a rapidly developing research area. This book deals with its critical issues, ranging from theoretical advances to practical applications. The introductory chapter outlines state-of-the-art earthquake modeling approaches based on stochastic models. Chapter 2 presents seismogenesis in association with the evolving stress field. Chapters 3 to 5 present earthquake occurrence modeling by means of hidden (semi-)Markov models and discuss associated characteristic measures and relative estimation aspects. Further comparisons, the most important results and our concluding remarks are provided in Chapters 6 and 7.

ICASSP 89

ICASSP 89
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1989
  • Pages : 2833
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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A Hidden Markov Renewal Model

A Hidden Markov Renewal Model
A Book

by Benjamin Preston

  • Publisher : Unknown Publisher
  • Release : 2015
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Hidden semi-Markov models (HSMMs) are a powerful class of statistical model that have been applied to a wide range of areas such as speech recognition, protein structure prediction, Internet-traffic modeling, financial time-series modeling, and classification of music. Three basic problems of hidden Markov model inference are: Computation of the likelihood, computation of the maximum likelihood-estimate of the model parameters, and computation of the maximum a posteriori estimate of the hidden state sequence. We address these inference problems for a set of models closely related to HSMMs. Our contributions are: (i) We extend the HSMM to allow observations to depend not only on the current underlying hidden state, but on the next underlying hidden state also. This extension can be used to model behavior whereby the observed data gradually transitions between states, rather than abruptly. (ii) We formulate the hidden portion of the model as a Markov renewal process. This allows us to naturally perform inference on models with hidden events other than state changes, e.g., jumps. (iii) We show that by augmenting the state space of our hidden Markov renewal model (HMRM), we can perform inference on an even larger class of phenomena, including models with stochastic volatility. Hence our HMRM can address three key areas of modern financial time series: regime-switching, jumps, and stochastic volatility. We develop algorithms to solve the three basic problems of inference for the HMRM. We validate the algorithms by performing inference on simulated data. We apply our model to two real-world datasets appearing in previously published analyses. The first dataset contains the log-returns of four European sector indices. Specifications of the HMRM improve the modeling of the auto-correlation function of squared returns compared to the HSMMs used in this first analysis. The second dataset consists of weekly returns from a weighted portfolio of NYSE stocks. Another specification of the HMRM gives improved volatility forecasts compared to the regime-switching GARCH models published in the second analysis.

Bayesian Inference and Maximum Entropy Methods in Science and Engineering

Bayesian Inference and Maximum Entropy Methods in Science and Engineering
26th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering

by Ali Mohammad-Djafari

  • Publisher : American Inst. of Physics
  • Release : 2006-12-13
  • Pages : 589
  • ISBN : 9780735403710
  • Language : En, Es, Fr & De
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The MaxEnt workshops are devoted to Bayesian inference and maximum entropy methods in science and engineering. In addition, this workshop included all aspects of probabilistic inference, such as foundations, techniques, algorithms, and applications. All papers have been peer-reviewed.

Data-Driven Modeling for Sustainable Engineering

Data-Driven Modeling for Sustainable Engineering
Proceedings of the First International Conference on Engineering, Applied Sciences and System Modeling (ICEASSM), Accra, 2017

by Kondo H. Adjallah,Babiga Birregah,Henry Fonbeyin Abanda

  • Publisher : Springer
  • Release : 2019-08-13
  • Pages : 425
  • ISBN : 3030136973
  • Language : En, Es, Fr & De
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This book gathers the proceedings of the 1st International Conference on Engineering, Applied Sciences and System Modeling (ICEASSM), a four-day event (18th–21st April 2017) held in Accra, Ghana. It focuses on research work promoting a better understanding of engineering problems through applied sciences and modeling, and on solutions generated in an African setting but with relevance to the world as a whole. The book provides a holistic overview of challenges facing Africa, and addresses various areas from research and development perspectives. Presenting contributions by scientists, engineers and experts hailing from a host of international institutions, the book offers original approaches and technological solutions to help solve real-world problems through research and knowledge sharing. Further, it explores promising opportunities for collaborative research on issues of scientific, economic and social development, making it of interest to researchers, scientists and practitioners looking to conduct research in disciplines such as water supply, control, civil engineering, statistical modeling, renewable energy and sustainable urban development.

Hidden Markov Models

Hidden Markov Models
Estimation and Control

by Robert J Elliott,Lakhdar Aggoun,John B. Moore

  • Publisher : Springer Science & Business Media
  • Release : 2008-09-27
  • Pages : 382
  • ISBN : 0387848541
  • Language : En, Es, Fr & De
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As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.

Statistical Theory and Method Abstracts

Statistical Theory and Method Abstracts
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2000
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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ICASSP 87

ICASSP 87
Proceedings, 1987 International Conference on Acoustics, Speech, and Signal Processing, April 6, 7, 8, 9, 1987, Registry Hotel, Dallas Texas

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1987
  • Pages : 2425
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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EMBC 2004

EMBC 2004
26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : Conference Proceedings : Linkages for Innovation in Biomedicine : 1-5 September, 2004, San Francisco, California

by IEEE Engineering in Medicine and Biology Society. Conference,IEEE Engineering in Medicine and Biology Society

  • Publisher : IEEE Computer Society Press
  • Release : 2004
  • Pages : 5459
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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"IEEE Catalog Number: 04CH37558"--T.p. verso.

Agronomie

Agronomie
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1999
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence and the Twentieth Innovative Applications of Artificial Intelligence Conference

Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence and the Twentieth Innovative Applications of Artificial Intelligence Conference
13-17 July 2008, Chicago, Illinois

by American Association for Artificial Intelligence

  • Publisher : Unknown Publisher
  • Release : 2008
  • Pages : 636
  • ISBN : 9781577353683
  • Language : En, Es, Fr & De
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Graphical Models

Graphical Models
Bayesian Networks, Markov Models, Markov Chain, Queueing Theory, Snakes and Ladders, Hidden Markov Model, Poisson Process, Reinforce

by Source Wikipedia

  • Publisher : University-Press.org
  • Release : 2013-09
  • Pages : 104
  • ISBN : 9781230553887
  • Language : En, Es, Fr & De
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 102. Chapters: Bayesian networks, Markov models, Markov chain, Queueing theory, Snakes and ladders, Hidden Markov model, Poisson process, Reinforcement learning, Burst error, Mark V Shaney, Kalman filter, PageRank, Multiple sequence alignment, Models of DNA evolution, Forward-backward algorithm, Path dependence, Belief propagation, Structural equation modeling, Viterbi algorithm, Algorithmic composition, Part-of-speech tagging, Gene prediction, Google matrix, Markov switching multifractal, Conditional random field, Influence diagram, Markov random field, Markov chain Monte Carlo, Bayesian inference in phylogeny, Graphical models for protein structure, Queueing model, Pop music automation, Dynamic Markov compression, Subshift of finite type, Stochastic matrix, Language model, Examples of Markov chains, Hierarchical Bayes model, Factor graph, Markov property, Path analysis, Detailed balance, Bernoulli scheme, Variational message passing, Latent variable, Layered hidden Markov model, Markov partition, Hierarchical hidden Markov model, Discrete phase-type distribution, GLIMMER, Kolmogorov backward equations, Baum-Welch algorithm, Dependability state model, Plate notation, Junction tree algorithm, Variable-order Bayesian network, Iterative Viterbi decoding, Markovian discrimination, Forward algorithm, Entropy rate, Hidden semi-Markov model, Maximum entropy Markov model, Population process, Markov blanket, Collider, Soft output Viterbi algorithm, Moral graph, M-separation, Dynamics of Markovian particles, Markov chain geostatistics, Quantum Markov chain, Transiogram, Ancestral graph, Causal Markov condition, Poisson hidden Markov model, Dynamic Bayesian network.