Hidden Semi Markov Models

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  • Publisher : Morgan Kaufmann
  • Release : 22 October 2015
  • ISBN : 9780128027714
  • Page : 208 pages
  • Rating : 4.5/5 from 103 voters

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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.

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Hidden Semi-Markov Models

Hidden Semi-Markov Models
  • Author : Shun-Zheng Yu
  • Publisher : Morgan Kaufmann
  • Release Date : 2015-10-22
  • ISBN : 9780128027714
GET THIS BOOKHidden Semi-Markov Models

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

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
  • ISBN : 9780387731735
GET THIS BOOKSemi-Markov Chains and Hidden Semi-Markov Models toward Applications

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

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
  • ISBN : 9781315355207
GET THIS BOOKHidden Markov Models for Time Series

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

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 : 2018
  • ISBN : 9781108421607
GET THIS BOOKIntroduction to Hidden Semi-Markov Models

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

Inference in Hidden Markov Models

Inference in Hidden Markov Models
  • Author : Olivier Cappé,Eric Moulines,Tobias Ryden
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-04-18
  • ISBN : 9780387289823
GET THIS BOOKInference in Hidden Markov Models

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

Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling
  • Author : Oliver Ibe
  • Publisher : Newnes
  • Release Date : 2013-05-22
  • ISBN : 9780124078390
GET THIS BOOKMarkov Processes for Stochastic Modeling

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

Hidden Semi-Markov Models

Hidden Semi-Markov Models
  • Author : Shun-Zheng Yu
  • Publisher : Morgan Kaufmann
  • Release Date : 2015-11-15
  • ISBN : 0128027673
GET THIS BOOKHidden Semi-Markov Models

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

Semi-Markov Models

Semi-Markov Models
  • Author : Yuriy E Obzherin,Elena G Boyko
  • Publisher : Academic Press
  • Release Date : 2015-02-03
  • ISBN : 9780128024867
GET THIS BOOKSemi-Markov Models

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,

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,Helmut Hlavacs,Wilfried Gansterer
  • Publisher : Springer
  • Release Date : 2011-12-13
  • ISBN : 9783642255755
GET THIS BOOKPerformance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

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

The Application of Hidden Markov Models in Speech Recognition

The Application of Hidden Markov Models in Speech Recognition
  • Author : Mark Gales,Steve Young
  • Publisher : Now Publishers Inc
  • Release Date : 2008
  • ISBN : 9781601981202
GET THIS BOOKThe Application of Hidden Markov Models in Speech Recognition

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.

Advanced Hybrid Information Processing

Advanced Hybrid Information Processing
  • Author : Guan Gui,Lin Yun
  • Publisher : Springer Nature
  • Release Date : 2019-11-28
  • ISBN : 9783030364052
GET THIS BOOKAdvanced Hybrid Information Processing

This two-volume set LNICST 301 -302 constitutes the post-conference proceedings of the Third EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2019, held in Nanjing, China, in September 2019. The 101 papers presented were selected from 237 submissions and focus on hybrid big data processing. Since information processing has acted as an important research domain in science and technology today, it is now to develop deeper and wider use of hybrid information processing, especially information processing for big data. There are more remaining issues

Markov Processes and Applications

Markov Processes and Applications
  • Author : Etienne Pardoux
  • Publisher : John Wiley & Sons
  • Release Date : 2008-11-20
  • ISBN : 9780470721865
GET THIS BOOKMarkov Processes and Applications

"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

Modeling Event Driven Time Series with Generalized Hidden Semi-Markov Models

Modeling Event Driven Time Series with Generalized Hidden Semi-Markov Models
  • Author : Felix Salfner
  • Publisher : Unknown
  • Release Date : 2006
  • ISBN : OCLC:180741985
GET THIS BOOKModeling Event Driven Time Series with Generalized Hidden Semi-Markov Models

Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms
  • Author : Giuseppe Bonaccorso
  • Publisher : Packt Publishing Ltd
  • Release Date : 2018-05-25
  • ISBN : 9781788625906
GET THIS BOOKMastering Machine Learning Algorithms

Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its

Efficient Learning Machines

Efficient Learning Machines
  • Author : Mariette Awad,Rahul Khanna
  • Publisher : Apress
  • Release Date : 2015-04-27
  • ISBN : 9781430259909
GET THIS BOOKEfficient Learning Machines

Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their