Inference in Hidden Markov Models

Author: Olivier Cappé,Eric Moulines,Tobias Ryden

Publisher: Springer Science & Business Media

ISBN: 0387289828

Category: Mathematics

Page: 653

View: 7963

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.

Wahrscheinlichkeitstheorie und Stochastische Prozesse

Author: Michael Mürmann

Publisher: Springer-Verlag

ISBN: 364238160X

Category: Mathematics

Page: 428

View: 8863

Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

Mustererkennung mit Markov-Modellen

Theorie — Praxis — Anwendungsgebiete

Author: Gernot A. Fink

Publisher: Springer-Verlag

ISBN: 3322800652

Category: Computers

Page: 233

View: 1513

Mustererkennung bildet die Grundlage für die Lösung verschiedenster Problembereiche in der Informatik. Spracherkennung, Schrifterkennung, Analyse biologischer Sequenzen: mit diesem Lehrbuch gelingt Ihnen der fundierte Einstieg in Theorie und Praxis.

Hidden Markov Models for Time Series

An Introduction Using R, Second Edition

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

Publisher: CRC Press

ISBN: 1482253844

Category: Mathematics

Page: 370

View: 4709

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

Applications in Computer Vision

Author: Horst Bunke,Terry Caelli

Publisher: World Scientific

ISBN: 9814491470

Category: Computers

Page: 244

View: 7183

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.

Grammatical Inference: Algorithms and Applications

6th International Colloquium: ICGI 2002, Amsterdam, The Netherlands, September 23-25, 2002. Proceedings

Author: Pieter Adriaans,Henning Fernau,Menno van Zaanen

Publisher: Springer

ISBN: 3540457909

Category: Computers

Page: 318

View: 4203

The Sixth International Colloquium on Grammatical Inference (ICGI2002) was held in Amsterdam on September 23-25th, 2002. ICGI2002 was the sixth in a series of successful biennial international conferenceson the area of grammatical inference. Previous meetings were held in Essex, U.K.; Alicante, Spain; Mo- pellier, France; Ames, Iowa, USA; Lisbon, Portugal. This series of meetings seeks to provide a forum for the presentation and discussion of original research on all aspects of grammatical inference. Gr- matical inference, the process of inferring grammars from given data, is a ?eld that not only is challenging from a purely scienti?c standpoint but also ?nds many applications in real-world problems. Despite the fact that grammatical inference addresses problems in a re- tively narrow area, it uses techniques from many domains, and is positioned at the intersection of a number of di?erent disciplines. Researchers in grammatical inference come from ?elds as diverse as machine learning, theoretical computer science, computational linguistics, pattern recognition, and arti?cial neural n- works. From a practical standpoint, applications in areas like natural language - quisition, computational biology, structural pattern recognition, information - trieval, text processing, data compression and adaptive intelligent agents have either been demonstrated or proposed in the literature. The technical program included the presentation of 23 accepted papers (out of 41 submitted). Moreover, for the ?rst time a software presentation was or- nized at ICGI. Short descriptions of the corresponding software are included in these proceedings, too.

Logische Grundlagen der Künstlichen Intelligenz

Author: Nils J. Nilsson

Publisher: Springer-Verlag

ISBN: 3322928810

Category: Technology & Engineering

Page: 576

View: 1491

Das Buch ist die deutsche Übersetzung des Standardwerkes der Stanforder Professoren Michael R. Genesereth und Nils J. Nilsson.Im Unterschied zu deutschen Lehrbüchern der Informatik zeichnet sich das Buch dadurch aus, daß es einen gut lesbaren Überblick gibt, ohne allzu formalistisch zu werden, gleichwohl aber von hohem Niveau ist und die Ergebnisse jüngster Forschung berücksichtigt. Das Buch empfiehlt sich sowohl für Studenten und Dozenten der Inf ormatik, aber auch für Forscher aus anderen Gebieten, die von den Grundlagen der Künstlichen Intelligenz profitieren möchten.

Computer Vision - ECCV 2002

7th European Conference on Computer Vision, Copenhagen, Denmark, May 28-31, 2002, Proceedings

Author: Anders Heyden,Gunnar Sparr,Mads Nielsen,Peters Johansen

Publisher: Springer Science & Business Media

ISBN: 3540437460

Category: Computers

Page: 919

View: 2120

Premiering in 1990 in Antibes, France, the European Conference on Computer Vision, ECCV, has been held biennially at venues all around Europe. These conferences have been very successful, making ECCV a major event to the computer vision community. ECCV 2002 was the seventh in the series. The privilege of organizing it was shared by three universities: The IT University of Copenhagen, the University of Copenhagen, and Lund University, with the conference venue in Copenhagen. These universities lie ̈ geographically close in the vivid Oresund region, which lies partly in Denmark and partly in Sweden, with the newly built bridge (opened summer 2000) crossing the sound that formerly divided the countries. We are very happy to report that this year’s conference attracted more papers than ever before, with around 600 submissions. Still, together with the conference board, we decided to keep the tradition of holding ECCV as a single track conference. Each paper was anonymously refereed by three different reviewers. For the nal selection, for the rst time for ECCV, a system with area chairs was used. These met with the program chairsinLundfortwodaysinFebruary2002toselectwhatbecame45oralpresentations and 181 posters.Also at this meeting the selection was made without knowledge of the authors’identity.

Bayesian Time Series Models

Author: David Barber,A. Taylan Cemgil,Silvia Chiappa

Publisher: Cambridge University Press

ISBN: 0521196760

Category: Computers

Page: 417

View: 2728

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

Issues in Biological and Life Sciences Research: 2011 Edition

Author: N.A

Publisher: ScholarlyEditions

ISBN: 1464963355

Category: Science

Page: 5106

View: 4904

Issues in Biological and Life Sciences Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biological and Life Sciences Research. The editors have built Issues in Biological and Life Sciences Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biological and Life Sciences Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biological and Life Sciences Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at

Methoden wissensbasierter Systeme

Grundlagen, Algorithmen, Anwendungen

Author: Christoph Beierle,Gabriele Kern-Isberner

Publisher: Springer-Verlag

ISBN: 3834823007

Category: Computers

Page: 545

View: 1628

Von namhaften Professoren empfohlen: State-of-the-Art bietet das Buch zu diesem klassischen Bereich der Informatik. Die wesentlichen Methoden wissensbasierter Systeme werden verständlich und anschaulich dargestellt. Repräsentation und Verarbeitung sicheren und unsicheren Wissens in maschinellen Systemen stehen dabei im Mittelpunkt. Ein Online-Service mit ausführlichen Musterlösungen erleichtert das Lernen.

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: 7399

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.

Inductive Logic Programming

18th International Conference, ILP 2008 Prague, Czech Republic, September 10-12, 2008, Proceedings

Author: Filip Železný,Nada Lavrač

Publisher: Springer Science & Business Media

ISBN: 3540859276

Category: Computers

Page: 347

View: 5540

This book constitutes the refereed proceedings of the 18th International Conference on Inductive Logic Programming, ILP 2008, held in Prague, Czech Republic, in September 2008. The 20 revised full papers presented together with the abstracts of 5 invited lectures were carefully reviewed and selected during two rounds of reviewing and improvement from 46 initial submissions. All current topics in inductive logic programming are covered, ranging from theoretical and methodological issues to advanced applications. The papers present original results in the first-order logic representation framework, explore novel logic induction frameworks, and address also new areas such as statistical relational learning, graph mining, or the semantic Web.