Hidden Markov Models and Dynamical Systems

Author: Andrew M. Fraser

Publisher: SIAM

ISBN: 0898717744

Category: Computer algorithms

Page: 132

View: 2376

This text provides an introduction to hidden Markov models (HMMs) for the dynamical systems community. It is a valuable text for third or fourth year undergraduates studying engineering, mathematics, or science that includes work in probability, linear algebra and differential equations. The book presents algorithms for using HMMs, and it explains the derivation of those algorithms. It presents Kalman filtering as the extension to a continuous state space of a basic HMM algorithm. The book concludes with an application to biomedical signals. This text is distinctive for providing essential introductory material as well as presenting enough of the theory behind the basic algorithms so that the reader can use it as a guide to developing their own variants.

Graphical Models

Foundations of Neural Computation

Author: Michael Irwin Jordan,Terrence Joseph Sejnowski,Tomaso A. Poggio

Publisher: MIT Press

ISBN: 9780262600422

Category: Computers

Page: 421

View: 7648

This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss

Entropy of Hidden Markov Processes and Connections to Dynamical Systems

Papers from the Banff International Research Station Workshop

Author: Brian Marcus,Karl Petersen,Tsachy Weissman

Publisher: Cambridge University Press

ISBN: 1139495747

Category: Mathematics

Page: N.A

View: 8596

Hidden Markov processes (HMPs) are important objects of study in many areas of pure and applied mathematics, including information theory, probability theory, dynamical systems and statistical physics, with applications in electrical engineering, computer science and molecular biology. This collection of research and survey papers presents important new results and open problems, serving as a unifying gateway for researchers in these areas. Based on talks given at the Banff International Research Station Workshop, 2007, this volume addresses a central problem of the subject: computation of the Shannon entropy rate of an HMP. This is a key quantity in statistical physics and information theory, characterising the fundamental limit on compression and closely related to channel capacity, the limit on reliable communication. Also discussed, from a symbolic dynamics and thermodynamical viewpoint, is the problem of characterizing the mappings between dynamical systems which map Markov measures to Markov (or Gibbs) measures, and which allow for Markov lifts of Markov chains.

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: 2106

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.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings

Author: Toon Calders,Floriana Esposito,Eyke Hüllermeier,Rosa Meo

Publisher: Springer

ISBN: 3662448513

Category: Computers

Page: 715

View: 4092

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

Speech Processing

A Dynamic and Optimization-Oriented Approach

Author: Li Deng,Douglas O'Shaughnessy

Publisher: CRC Press

ISBN: 9780824740405

Category: Technology & Engineering

Page: 752

View: 3365

Based on years of instruction and field expertise, this volume offers the necessary tools to understand all scientific, computational, and technological aspects of speech processing. The book emphasizes mathematical abstraction, the dynamics of the speech process, and the engineering optimization practices that promote effective problem solving in this area of research and covers many years of the authors' personal research on speech processing. Speech Processing helps build valuable analytical skills to help meet future challenges in scientific and technological advances in the field and considers the complex transition from human speech processing to computer speech processing.

Hidden Markov Models

Applications in Computer Vision

Author: Horst Bunke,Terry Caelli

Publisher: World Scientific

ISBN: 9814491470

Category: Computers

Page: 244

View: 9524

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.

Adaptive Processing of Sequences and Data Structures

International Summer School on Neural Networks, "E.R. Caianiello", Vietri Sul Mare, Salerno, Italy, September 6-13, 1997, Tutorial Lectures

Author: C.Lee Giles,Marco Gori

Publisher: Springer Science & Business Media

ISBN: 9783540643418

Category: Computers

Page: 434

View: 5319

Tenascin, a recently characterized extracellular matrix (ECM) protein which is expressed during embryonic and fetal development, wound healing and various benign and malignant tumors (but highly restricted in normal adult tissues) is believed to affect a number of cellular functions such as cellular growth, differentiation, adhesion and motility. It has been extensively studied in recent years to elucidate cellular phenomena that are associated with development, tissue regeneration and neoplastic growth and behavior. It may be a potential target in the treatment of cancers and other disorders. This book focuses mainly on tissue expression and the poorly known biological role of this ECM protein.

AAAI 99

Author: N.A

Publisher: Aaai Press

ISBN: N.A

Category: Computers

Page: 998

View: 1623

AAAI proceedings describe innovative concepts, techniques, perspectives, and observations that present promising research directions in artificial intelligence.

Pattern Recognition and Data Mining

Third International Conference on Advances in Pattern Recognition, ICAR 2005, Bath, UK, August 22-25, 2005

Author: Sameer Singh

Publisher: Springer Science & Business Media

ISBN: 9783540287575

Category: Computers

Page: 689

View: 8587

The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The first volume includes 73 contributions related to Pattern Recognition and Data Mining (which included papers from the tracks of pattern recognition methods, knowledge and learning, and data mining); topics addressed are pattern recognition, data mining, signal processing and OCR/ document analysis. The second volume contains 87 contributions related to Pattern Recognition and Image Analysis (which included papers from the applications track) and deals with security and surveillance, biometrics, image processing and medical imaging. It also contains papers from the Workshop on Pattern Recognition for Crime Prevention.

Automatic Speech Recognition

A Deep Learning Approach

Author: Dong Yu,Li Deng

Publisher: Springer

ISBN: 1447157796

Category: Technology & Engineering

Page: 321

View: 3695

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Hybrid Systems: Computation and Control

10th International Workshop, HSCC 2007, Pisa, Italy, April 3-5, 2007, Proceedings

Author: Alberto Bemporad

Publisher: Springer Science & Business Media

ISBN: 3540714928

Category: Computers

Page: 797

View: 4331

This book constitutes the refereed proceedings of the 10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007, held in Pisa, Italy in April 2007. The 44 revised full papers and 39 revised short papers presented together with the abstracts of 3 keynote talks were carefully reviewed and selected from 167 submissions. Among the topics addressed are models of heterogeneous systems, computability and complexity issues, real-time computing and control, embedded and resource-aware control, control and estimation over wireless networks, tools for analysis, verification, control, and design, programming languages support and implementation, applications, including automotive, communication networks, avionics, energy systems, transportation networks, biology and other sciences, manufacturing, and robotics.

Stochastic Modeling and Optimization

With Applications in Queues, Finance, and Supply Chains

Author: David D. Yao,Hanqin Zhang,Xun Yu Zhou

Publisher: Springer Science & Business Media

ISBN: 9780387955827

Category: Business & Economics

Page: 468

View: 7039

This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

Methods in Bioengineering

Systems Analysis of Biological Networks

Author: Arul Jayaraman,Juergen Hahn

Publisher: Artech House

ISBN: 1596934069

Category: Science

Page: 316

View: 2205

"This cutting-edge volume provides a detailed look at the two main aspects of systems biology: the design of sophisticated experimental methods and the development of complex models to analyze the data. Focusing on methods that are being used to solve current problems in biomedical science and engineering, this comprehensive, richly illustrated resource shows you how to: design of state-of-the art methods for analyzing biological systems Implement experimental approaches for investigating cellular behavior in health and disease; use algorithms and modeling techniques for quantitatively describing biomedical problems; and integrate experimental and computational approaches for a more complete view of biological systems." --Book Jacket.

Data Analysis, Machine Learning and Applications

Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007

Author: Christine Preisach,Hans Burkhardt,Lars Schmidt-Thieme,Reinhold Decker

Publisher: Springer Science & Business Media

ISBN: 9783540782469

Category: Computers

Page: 719

View: 5981

Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

Markov Chains: Models, Algorithms and Applications

Author: Wai-Ki Ching,Michael K. Ng

Publisher: Springer Science & Business Media

ISBN: 038729337X

Category: Mathematics

Page: 208

View: 7446

Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.

AI 2003: Advances in Artificial Intelligence

16th Australian Conference on AI, Perth, Australia, December 3-5, 2003, Proceedings

Author: Tamas D. Gedeon,Lance C.C. Fung

Publisher: Springer Science & Business Media

ISBN: 3540206469

Category: Computers

Page: 1075

View: 948

This book constitutes the refereed proceedings of the 16th Australian Conference on Artificial Intelligence, AI 2003, held in Perth, Australia in December 2003. The 87 revised full papers presented together with 4 keynote papers were carefully reviewed and selected from 179 submissions. The papers are organized in topical sections on ontologies, problem solving, knowledge discovery and data mining, expert systems, neural network applications, belief revision and theorem proving, reasoning and logic, machine learning, AI applications, neural computing, intelligent agents, computer vision, medical applications, machine learning and language, AI and business, soft computing, language understanding, and theory.

Nonlinear Dynamics and Chaos with Applications to Hydrodynamics and Hydrological Modelling

Author: Slavco Velickov

Publisher: CRC Press

ISBN: 9058096912

Category: Science

Page: 336

View: 5932

A hydroinformatics system represents an electronic knowledge encapsulator that models part of the real world and can be used for the simulation and analysis of physical, chemical and biological processes in water systems, in order to achieve a better management of the aquatic environment. Thus, modelling is at the heart of hydroinformatics. The theory of nonlinear dynamics and chaos, and the extent to which recent improvements in the understanding of inherently nonlinear natural processes present challenges to the use of mathematical models in the analysis of water and environmental systems, are elaborated in this work. In particular, it demonstrates that the deterministic chaos present in many nonlinear systems can impose fundamental limitations on our ability to predict behaviour, even when well-defined mathematical models exist. On the other hand, methodologies and tools from the theory of nonlinear dynamics and chaos can provide means for a better accuracy of short-term predictions as demonstrated through the practical applications in this work.