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

Their Use in Reliability and DNA Analysis

Author: Vlad Stefan Barbu,Nikolaos Limnios

Publisher: Springer Science & Business Media

ISBN: 0387731733

Category: Mathematics

Page: 226

View: 7217

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

Theory, Algorithms and Applications

Author: Shun-Zheng Yu

Publisher: Morgan Kaufmann

ISBN: 0128027711

Category: Computers

Page: 208

View: 9313

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

An Introduction Using R, Second Edition

Author: Walter Zucchini,Iain L. MacDonald,Roland Langrock

Publisher: CRC Press

ISBN: 1315355205

Category: Mathematics

Page: 370

View: 7967

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

Graphical Models

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

Author: Source Wikipedia

Publisher: University-Press.org

ISBN: 9781230553887

Category:

Page: 104

View: 9714

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.

Hidden Markov Models

Estimation and Control

Author: Robert J Elliott,Lakhdar Aggoun,John B. Moore

Publisher: Springer Science & Business Media

ISBN: 0387848541

Category: Science

Page: 382

View: 1380

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.

Semi-Markov Models

Theory and Applications

Author: Jacques Janssen

Publisher: Springer Science & Business Media

ISBN: 148990574X

Category: Mathematics

Page: 588

View: 6610

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.

STAIRS 2014

Proceedings of the 7th European Starting AI Researcher Symposium

Author: U. Endriss,J. Leite

Publisher: IOS Press

ISBN: 1614994218

Category: Computers

Page: 316

View: 3812

Artificial Intelligence is a field which continues to expand and develop rapidly, and so it is also one in which original ideas and fresh perspectives are of particular interest. The Starting AI Researcher Symposium (STAIRS) is an international meeting which supports Ph.D. students and those who have held a Ph.D. for less than one year, from all over the world, at the start of their career. The symposium offers doctoral students and young postdoctoral AI fellows the chance to experience delivering a presentation of their work in a supportive environment. This book presents papers from the Seventh STAIRS, a satellite event of the 21st European Conference on Artificial Intelligence (ECAI) held in Prague, Czech Republic, in August 2014. The book includes 30 papers accepted for presentation at the conference, out of 45 submissions. 16 papers were selected for an oral presentation at the symposium, while the other 14 were presented at a poster session. Together these papers cover the field of AI; knowledge representation and reasoning, machine learning, planning and scheduling being the areas which have attracted the largest number of submissions. The book provides a fascinating preview of the current work of future AI researchers, and will be of interest to all those whose work involves the use of artificial intelligence and intelligent systems.

Handbook on Soft Computing for Video Surveillance

Author: Sankar K. Pal,Alfredo Petrosino,Lucia Maddalena

Publisher: CRC Press

ISBN: 1439856842

Category: Mathematics

Page: 342

View: 5500

Information on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Worldwide experts in the field present novel solutions to video surveillance problems and discuss future trends. After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems under development. Incorporating both existing and new ideas, this handbook unifies the basic concepts, theories, algorithms, and applications of soft computing. It demonstrates why and how soft computing methodologies can be used in various video surveillance problems.

Progress in Pattern Recognition

Author: Sameer Singh,Maneesha Singh

Publisher: Springer Science & Business Media

ISBN: 9781846289446

Category: Computers

Page: 243

View: 8631

This book features a collection of articles presented at the 2007 Workshop on Advances in Pattern Recognition, which was organized in conjunction with the 5th International Summer School on Pattern Recognition. It provides readers with the state-of-the-art algorithms in the area of pattern recognition as well as a presentation of the cutting edge applications within the field.

Intelligent Diagnosis and Prognosis of Industrial Networked Systems

Author: Chee Khiang Pang,Frank L. Lewis,Tong Heng Lee,Zhao Yang Dong

Publisher: CRC Press

ISBN: 1439840598

Category: Computers

Page: 332

View: 3917

In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.

Markov Models for Pattern Recognition

From Theory to Applications

Author: Gernot A. Fink

Publisher: Springer Science & Business Media

ISBN: 1447163087

Category: Computers

Page: 276

View: 6926

This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Systeme der Regelungstechnik mit MATLAB und Simulink

Analyse und Simulation

Author: Helmut Bode

Publisher: Walter de Gruyter

ISBN: 3486769707

Category: Technology & Engineering

Page: 445

View: 8179

Das Werk behandelt die Einsatzmöglichkeiten von MATLAB® und Simulink® in der Regelungstechnik zur Analyse und Simulation dynamischer Systeme. Exemplarische regelungstechnische Probleme werden modelliert und simuliert. Aufgrund der sehr elementaren Darstellung ist das Buch ausgezeichnet für den Einsatz in der Lehre geeignet. Die eingesetzten MATLAB®-Codes stehen zum Download bereit. Die 2., aktualisierte Auflage ist an die aktuelle MATLAB®-Version 8.1.0.604 (R2013a) angepasst.

ICASSP 85

proceedings, March 26-29, 1985, Hyatt Regency Hotel, Tampa, Florida

Author: IEEE Acoustics, Speech, and Signal Processing Society

Publisher: N.A

ISBN: N.A

Category: Technology & Engineering

Page: 1861

View: 8834


Advances in Neural Information Processing Systems 19

Proceedings of the 2006 Conference

Author: Bernhard Schölkopf,John Platt,Thomas Hofmann

Publisher: MIT Press

ISBN: 0262195682

Category: Computers

Page: 1643

View: 358

The annual conference on NIPS is the flagship conference on neural computation. It draws top academic researchers from around the world & is considered to be a showcase conference for new developments in network algorithms & architectures. This volume contains all of the papers presented at NIPS 2006.

Applications of Data Mining in E-Business and Finance

Author: C. Soares,Y. Peng,J. Meng

Publisher: IOS Press

ISBN: 1607503549

Category: Business & Economics

Page: 156

View: 712

The application of Data Mining (DM) technologies has shown an explosive growth in an increasing number of different areas of business, government and science. Two of the most important business areas are finance, in particular in banks and insurance companies, and e-business, such as web portals, e-commerce and ad management services. In spite of the close relationship between research and practice in Data Mining, it is not easy to find information on some of the most important issues involved in real world application of DM technology, from business and data understanding to evaluation and deployment. Papers often describe research that was developed without taking into account constraints imposed by the motivating application. When these issues are taken into account, they are frequently not discussed in detail because the paper must focus on the method. Therefore knowledge that could be useful for those who would like to apply the same approach on a related problem is not shared. The papers in this book address some of these issues. This book is of interest not only to Data Mining researchers and practitioners, but also to students who wish to have an idea of the practical issues involved in Data Mining.