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

Author: Vlad Stefan Barbu

Publisher: Springer Science & Business Media

Published: 2009-01-07

Total Pages: 233

ISBN-13: 0387731733

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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

Published: 2015-10-22

Total Pages: 209

ISBN-13: 0128027711

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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 Markov Models for Time Series
Hidden Markov Models for Time Series

Author: Walter Zucchini

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 370

ISBN-13: 1482253844

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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

Introduction to Hidden Semi-Markov Models
Introduction to Hidden Semi-Markov Models

Author: John Van der Hoek

Publisher: Cambridge University Press

Published: 2018

Total Pages: 185

ISBN-13: 1108421601

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Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state framework suitable for senior undergraduates and graduates. The authors then introduce semi-Markov chains and hidden semi-Markov chains, before developing related estimation and filtering results. Genomics applications are modelled by discrete observations of these hidden semi-Markov chains. This book contains new results and previously unpublished material not available elsewhere. The approach is rigorous and focused on applications

Inference in Hidden Markov Models
Inference in Hidden Markov Models

Author: Olivier Cappé

Publisher: Springer Science & Business Media

Published: 2006-04-12

Total Pages: 656

ISBN-13: 0387289828

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This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

Statistical Topics and Stochastic Models for Dependent Data with Applications
Statistical Topics and Stochastic Models for Dependent Data with Applications

Author: Vlad Stefan Barbu

Publisher: John Wiley & Sons

Published: 2020-12-03

Total Pages: 288

ISBN-13: 1786306034

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This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.

The Application of Hidden Markov Models in Speech Recognition
The Application of Hidden Markov Models in Speech Recognition

Author: Mark Gales

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 125

ISBN-13: 1601981201

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The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.

Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges
Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

Author: Karin Anna Hummel

Publisher: Springer

Published: 2011-12-13

Total Pages: 266

ISBN-13: 3642255752

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This Festschrift volume is published in honor of Günter Haring on the occasion of his emerital celebration and contains invited papers by key researchers in the field of performance evaluation presented at the workshop Performance Evaluation of Computer and Communication Systems - Milestones and Future Challenges, PERFORM 2010, held in Vienna, Austria, in October 2010. Günter Haring has dedicated most of his scientific professional life to performance evaluation and the design of distributed systems, contributing in particular to the field of workload characterization. In addition to his own contributions and leadership in international research projects, he is and has been an excellent mentor of young researchers demonstrated by their own brilliant scientific careers. The 20 thoroughly refereed papers range from visionary to in-depth research papers and are organized in the following topical sections: milestones and evolutions; trends: green ICT and virtual machines; modeling; mobility and mobile networks; communication and computer networks; and load balancing, analysis, and management.

Hidden Markov and Other Models for Discrete- valued Time Series
Hidden Markov and Other Models for Discrete- valued Time Series

Author: Iain L. MacDonald

Publisher: CRC Press

Published: 1997-01-01

Total Pages: 256

ISBN-13: 9780412558504

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Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been developed which are specifically designed for the analysis of discrete-valued time series. Hidden Markov and Other Models for Discrete-Valued Time Series introduces a new, versatile, and computationally tractable class of models, the "hidden Markov" models. It presents a detailed account of these models, then applies them to data from a wide range of diverse subject areas, including medicine, climatology, and geophysics. This book will be invaluable to researchers and postgraduate and senior undergraduate students in statistics. Researchers and applied statisticians who analyze time series data in medicine, animal behavior, hydrology, and sociology will also find this information useful.