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Hidden Semi Markov Models

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Hidden Semi Markov Models

Hidden Semi Markov Models Book
Author : Shun-Zheng Yu
Publisher : Morgan Kaufmann
Release : 2015-11-15
ISBN : 9780128027677
Language : En, Es, Fr & De

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Book Description :

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.

Semi Markov Chains and Hidden Semi Markov Models toward Applications

Semi Markov Chains and Hidden Semi Markov Models toward Applications Book
Author : Vlad Stefan Barbu,Nikolaos Limnios
Publisher : Springer Science & Business Media
Release : 2009-01-07
ISBN : 0387731733
Language : En, Es, Fr & De

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Book Description :

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 Markov Models for Time Series

Hidden Markov Models for Time Series Book
Author : Walter Zucchini,Iain L. MacDonald,Roland Langrock
Publisher : CRC Press
Release : 2017-12-19
ISBN : 1315355205
Language : En, Es, Fr & De

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Book Description :

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 Book
Author : John Van der Hoek,Robert J. Elliott
Publisher : Cambridge University Press
Release : 2019
ISBN : 1108421601
Language : En, Es, Fr & De

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Book Description :

Develops the theory of Markov and semi-Markov processes in an elementary setting suitable for senior undergraduate and graduate students.

Inference in Hidden Markov Models

Inference in Hidden Markov Models Book
Author : Olivier Cappé,Eric Moulines,Tobias Ryden
Publisher : Springer Science & Business Media
Release : 2006-04-18
ISBN : 0387289828
Language : En, Es, Fr & De

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Book Description :

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.

Hidden Semi Markov Models

Hidden Semi Markov Models Book
Author : Shun-Zheng Yu
Publisher : Morgan Kaufmann
Release : 2015-10-22
ISBN : 0128027711
Language : En, Es, Fr & De

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Book Description :

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.

Fitting Hidden Semi Markov Models

Fitting Hidden Semi Markov Models Book
Author : Anonim
Publisher : Unknown
Release : 2000
ISBN : 9780478232028
Language : En, Es, Fr & De

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Book Description :

Download Fitting Hidden Semi Markov Models book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Hidden Markov and Other Models for Discrete valued Time Series

Hidden Markov and Other Models for Discrete  valued Time Series Book
Author : Iain L. MacDonald,Walter Zucchini
Publisher : CRC Press
Release : 1997-01-01
ISBN : 9780412558504
Language : En, Es, Fr & De

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Book Description :

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.

Semi Markov Models

Semi Markov Models Book
Author : Yuriy E Obzherin,Elena G Boyko
Publisher : Academic Press
Release : 2015-02-03
ISBN : 0128024860
Language : En, Es, Fr & De

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Book Description :

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and utilizing the method of asymptotic phase enlargement developed by V.S. Korolyuk and A.F. Turbin. The work then explores semi-Markov models of latent failures control in two-component systems. Building on these results, solutions are provided for the problems of optimal periodicity of control execution. Finally, the book presents a comparative analysis of analytical and imitational modeling of some one- and two-component systems, before discussing practical applications of the results Reflects the possibility and effectiveness of this method of modeling systems, such as phase merging algorithms developed by V.S. Korolyuk, A.F. Turbin, A.V. Swishchuk, little covered elsewhere Focuses on possible applications to engineering control systems

Performance Evaluation of Computer and Communication Systems Milestones and Future Challenges

Performance Evaluation of Computer and Communication Systems  Milestones and Future Challenges Book
Author : Karin Anna Hummel,Helmut Hlavacs,Wilfried Gansterer
Publisher : Springer
Release : 2011-12-13
ISBN : 3642255752
Language : En, Es, Fr & De

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Book Description :

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.

Markov Processes and Applications

Markov Processes and Applications Book
Author : Etienne Pardoux
Publisher : John Wiley & Sons
Release : 2008-11-20
ISBN : 0470721863
Language : En, Es, Fr & De

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Book Description :

"This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications. The mathematical treatment is precise and rigorous without superfluous details, and the results are immediately illustrated in illuminating examples. This book will be extremely useful to anybody teaching a course on Markov processes." Jean-François Le Gall, Professor at Université de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally independent, given their present state. They constitute important models in many applied fields. After an introduction to the Monte Carlo method, this book describes discrete time Markov chains, the Poisson process and continuous time Markov chains. It also presents numerous applications including Markov Chain Monte Carlo, Simulated Annealing, Hidden Markov Models, Annotation and Alignment of Genomic sequences, Control and Filtering, Phylogenetic tree reconstruction and Queuing networks. The last chapter is an introduction to stochastic calculus and mathematical finance. Features include: The Monte Carlo method, discrete time Markov chains, the Poisson process and continuous time jump Markov processes. An introduction to diffusion processes, mathematical finance and stochastic calculus. Applications of Markov processes to various fields, ranging from mathematical biology, to financial engineering and computer science. Numerous exercises and problems with solutions to most of them

Speech Recognition and Coding

Speech Recognition and Coding Book
Author : Antonio J. Rubio Ayuso,Juan M. Lopez Soler
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 3642577458
Language : En, Es, Fr & De

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Book Description :

Based on a NATO Advanced Study Institute held in 1993, this book addresses recent advances in automatic speech recognition and speech coding. The book contains contributions by many of the most outstanding researchers from the best laboratories worldwide in the field. The contributions have been grouped into five parts: on acoustic modeling; language modeling; speech processing, analysis and synthesis; speech coding; and vector quantization and neural nets. For each of these topics, some of the best-known researchers were invited to give a lecture. In addition to these lectures, the topics were complemented with discussions and presentations of the work of those attending. Altogether, the reader is given a wide perspective on recent advances in the field and will be able to see the trends for future work.

Algorithmic Foundations of Robotics XIII

Algorithmic Foundations of Robotics XIII Book
Author : Marco Morales,Lydia Tapia,Gildardo Sánchez-Ante,Seth Hutchinson
Publisher : Springer Nature
Release : 2020-05-07
ISBN : 3030440516
Language : En, Es, Fr & De

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Book Description :

This book gathers the outcomes of the thirteenth Workshop on the Algorithmic Foundations of Robotics (WAFR), the premier event for showcasing cutting-edge research on algorithmic robotics. The latest WAFR, held at Universidad Politécnica de Yucatán in Mérida, México on December 9–11, 2018, continued this tradition. This book contains fifty-four papers presented at WAFR, which highlight the latest research on fundamental algorithmic robotics (e.g., planning, learning, navigation, control, manipulation, optimality, completeness, and complexity) demonstrated through several applications involving multi-robot systems, perception, and contact manipulation. Addressing a diverse range of topics in papers prepared by expert contributors, the book reflects the state of the art and outlines future directions in the field of algorithmic robotics.

Semi Markov Processes and Reliability

Semi Markov Processes and Reliability Book
Author : N. Limnios,G. Oprisan
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 1461201616
Language : En, Es, Fr & De

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Book Description :

At first there was the Markov property. The theory of stochastic processes, which can be considered as an exten sion of probability theory, allows the modeling of the evolution of systems through the time. It cannot be properly understood just as pure mathemat ics, separated from the body of experience and examples that have brought it to life. The theory of stochastic processes entered a period of intensive develop ment, which is not finished yet, when the idea of the Markov property was brought in. Not even a serious study of the renewal processes is possible without using the strong tool of Markov processes. The modern theory of Markov processes has its origins in the studies by A. A: Markov (1856-1922) of sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian mo tion. Later, many generalizations (in fact all kinds of weakenings of the Markov property) of Markov type stochastic processes were proposed. Some of them have led to new classes of stochastic processes and useful applications. Let us mention some of them: systems with complete connections [90, 91, 45, 86]; K-dependent Markov processes [44]; semi-Markov processes, and so forth. The semi-Markov processes generalize the renewal processes as well as the Markov jump processes and have numerous applications, especially in relia bility.

Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling Book
Author : Oliver Ibe
Publisher : Newnes
Release : 2013-05-22
ISBN : 0124078397
Language : En, Es, Fr & De

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Book Description :

Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.

Hidden Markov Models

Hidden Markov Models Book
Author : Horst Bunke,Terry Caelli
Publisher : World Scientific
Release : 2001-06-04
ISBN : 9814491470
Language : En, Es, Fr & De

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Book Description :

Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval. This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001). Contents: Introduction: A Simple Complex in Artificial Intelligence and Machine Learning (B H Juang)An Introduction to Hidden Markov Models and Bayesian Networks (Z Chahramani)Multi-Lingual Machine Printed OCR (P Natarajan et al.)Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System (U-V Marti & H Bunke)A 2-D HMM Method for Offline Handwritten Character Recognition (H-S Park et al.)Data-Driven Design of HMM Topology for Online Handwriting Recognition (J J Lee et al.)Hidden Markov Models for Modeling and Recognizing Gesture Under Variation (A D Wilson & A F Bobick)Sentence Lipreading Using Hidden Markov Model with Integrated Grammar (K Yu et al.)Tracking and Surveillance in Wide-Area Spatial Environments Using the Abstract Hidden Markov Model (H H Bui et al.)Shape Tracking and Production Using Hidden Markov Models (T Caelli et al.)An Integrated Approach to Shape and Color-Based Image Retrieval of Rotated Objects Using Hidden Markov Models (S Müller et al.) Readership: Graduate students of computer science, electrical engineering and related fields, as well as researchers at academic and industrial institutions. Keywords:Hidden Markov Models;Gesture Recognitoin;Bayesian Networks;Optical Character Recognition;Handwriting Character Recognition;Cartography;Shape Extraction;Image Feature Extraction.

The Application of Hidden Markov Models in Speech Recognition

The Application of Hidden Markov Models in Speech Recognition Book
Author : Mark Gales,Steve Young
Publisher : Now Publishers Inc
Release : 2008
ISBN : 1601981201
Language : En, Es, Fr & De

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Book Description :

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.

Robot Learning Human Skills and Intelligent Control Design

Robot Learning Human Skills and Intelligent Control Design Book
Author : Chenguang Yang,Chao Zeng,Jianwei Zhang
Publisher : CRC Press
Release : 2021-06-22
ISBN : 1000395170
Language : En, Es, Fr & De

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Book Description :

In the last decades robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn manipulation skills from humans. To this end, a number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book introduces recent results on the development of advanced LfD-based learning and control approaches to improve the robot dexterous manipulation. First, there's an introduction to the simulation tools and robot platforms used in the authors' research. In order to enable a robot learning of human-like adaptive skills, the book explains how to transfer a human user’s arm variable stiffness to the robot, based on the online estimation from the muscle electromyography (EMG). Next, the motion and impedance profiles can be both modelled by dynamical movement primitives such that both of them can be planned and generalized for new tasks. Furthermore, the book introduces how to learn the correlation between signals collected from demonstration, i.e., motion trajectory, stiffness profile estimated from EMG and interaction force, using statistical models such as hidden semi-Markov model and Gaussian Mixture Regression. Several widely used human-robot interaction interfaces (such as motion capture-based teleoperation) are presented, which allow a human user to interact with a robot and transfer movements to it in both simulation and real-word environments. Finally, improved performance of robot manipulation resulted from neural network enhanced control strategies is presented. A large number of examples of simulation and experiments of daily life tasks are included in this book to facilitate better understanding of the readers.

Hidden Markov Models

Hidden Markov Models Book
Author : Robert J Elliott,Lakhdar Aggoun,John B. Moore
Publisher : Springer Science & Business Media
Release : 2008-09-27
ISBN : 0387848541
Language : En, Es, Fr & De

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Book Description :

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.