May 9, 2021

Download Ebook Free Hidden Semi-Markov Models

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

Semi-Markov Chains and Hidden Semi-Markov Models toward Applications
Author : Vlad Stefan Barbu,Nikolaos Limnios
Publisher : Springer Science & Business Media
Release Date : 2009-01-07
Category : Mathematics
Total pages :226
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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
Author : Shun-Zheng Yu
Publisher : Morgan Kaufmann
Release Date : 2015-10-22
Category : Computers
Total pages :208
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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
Author : Christoph Anger
Publisher : Unknown
Release Date : 2018
Category : Maintenance
Total pages :129
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A Multivariate Hidden Semi-Markov Model of Customer-multichannel Engagement

A Multivariate Hidden Semi-Markov Model of Customer-multichannel Engagement
Author : Sharmistha Sikdar,Giles Hooker
Publisher : Unknown
Release Date : 2019
Category :
Total pages :129
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Introduction to Hidden Semi-Markov Models

Introduction to Hidden Semi-Markov Models
Author : John Van der Hoek,Robert J. Elliott
Publisher : Cambridge University Press
Release Date : 2019
Category : Hidden Markov models
Total pages :129
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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 Models

Semi-Markov Models
Author : Jacques Janssen
Publisher : Springer Science & Business Media
Release Date : 2013-11-11
Category : Mathematics
Total pages :588
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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.

Earthquake Statistical Analysis through Multi-state Modeling

Earthquake Statistical Analysis through Multi-state Modeling
Author : Irene Votsi,Nikolaos Limnios,Eleftheria Papadimitriou,Georgios Tsaklidis
Publisher : John Wiley & Sons
Release Date : 2019-04-02
Category : Mathematics
Total pages :180
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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.

Research Review

Research Review
Author : Anonim
Publisher : Unknown
Release Date : 1985
Category : Radar
Total pages :129
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Hidden Markov Models for Time Series

Hidden Markov Models for Time Series
Author : Walter Zucchini,Iain L. MacDonald,Roland Langrock
Publisher : CRC Press
Release Date : 2017-12-19
Category : Mathematics
Total pages :370
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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

Hidden Markov Models

Hidden Markov Models
Author : Robert J Elliott,Lakhdar Aggoun,John B. Moore
Publisher : Springer Science & Business Media
Release Date : 2008-09-27
Category : Science
Total pages :382
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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.

ICASSP 89

ICASSP 89
Author : Anonim
Publisher : Unknown
Release Date : 1989
Category : Electro-acoustics
Total pages :2833
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A Hidden Markov Renewal Model

A Hidden Markov Renewal Model
Author : Benjamin Preston
Publisher : Unknown
Release Date : 2015
Category : Markov processes
Total pages :129
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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
Author : Ali Mohammad-Djafari
Publisher : American Inst. of Physics
Release Date : 2006-12-13
Category : Science
Total pages :589
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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
Author : Kondo H. Adjallah,Babiga Birregah,Henry Fonbeyin Abanda
Publisher : Springer
Release Date : 2019-08-13
Category : Technology & Engineering
Total pages :425
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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.

Statistical Theory and Method Abstracts

Statistical Theory and Method Abstracts
Author : Anonim
Publisher : Unknown
Release Date : 2000
Category : Statistics
Total pages :129
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