Pattern Theory
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Pattern Theory
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Author : David Mumford
language : en
Publisher: CRC Press
Release Date : 2010-08-09
Pattern Theory written by David Mumford and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-09 with Computers categories.
Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes onlineaccess to thematerials (data, code, etc.) needed for the exercises.
Pattern Theory
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Author : Ulf Grenander
language : en
Publisher: Oxford University Press
Release Date : 2007
Pattern Theory written by Ulf Grenander and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website. The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes.
Pattern Theory
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Author : Rachel H. Ellaway
language : en
Publisher: Taylor & Francis
Release Date : 2024-12-30
Pattern Theory written by Rachel H. Ellaway and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Science categories.
Pattern Theory is a groundbreaking exploration of the concept of pattern across a range of disciplines, including science, neuroscience, psychology, and social sciences. This book examines the meaning and implications of pattern, presenting a comprehensive body of theory that unifies concepts of form, order, and regularity and connects them to memory and perception. By challenging existing orthodoxies and linking evidence from brain and mind function, it outlines a robust theoretical framework around pattern searching and matching, pattern activation, and the continuity of pattern nexuses. This in-depth study of pattern theory and pattern thinking delves into the cognitive basis of patterns, their impact on reasoning and learning, and the social and collaborative nature of pattern recognition, expression, and representation. It also addresses philosophical issues and implications surrounding shared pattern thinking and introduces a broad conceptual basis for "pattern inquiry", providing a range of questions and methodologies for applying pattern theory. The book culminates in a manifesto for pattern theory and its application in pattern inquiry, offering 50 key principles that can be applied across various settings. Researchers, scholars, and practitioners are encouraged to explore and critique this unified theory as a lens for examining social and cognitive phenomena. Ideal for academics and professionals seeking to challenge their understanding of the connections between mind and society, as well as for those looking to deepen their understanding of pattern as a cognitive phenomenon, as a theoretical lens, and as a meta-methodology for inquiry, this text provides a substantive foundation for ongoing development and application of pattern science across multiple fields.
A Probabilistic Theory Of Pattern Recognition
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Author : Luc Devroye
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-27
A Probabilistic Theory Of Pattern Recognition written by Luc Devroye and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-27 with Mathematics categories.
Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy, parametric classification, error estimation, free classifiers, and neural networks. Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material.
Information Theory In Computer Vision And Pattern Recognition
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Author : Francisco Escolano Ruiz
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-14
Information Theory In Computer Vision And Pattern Recognition written by Francisco Escolano Ruiz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-14 with Computers categories.
Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.
Elements Of Pattern Theory
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Author : Ulf Grenander
language : en
Publisher: JHU Press
Release Date : 1996
Elements Of Pattern Theory written by Ulf Grenander and has been published by JHU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Mathematics categories.
"A dazzling tour de force on patterns. It is a substantial, original contribution by a leader-indeed, originator-in the field, and has the potential for significant impact on the direction of future research." -- Alan F. Karr, National Institute of Statistical Sciences
General Pattern Theory
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Author : Ulf Grenander
language : en
Publisher:
Release Date : 1993
General Pattern Theory written by Ulf Grenander and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.
The aim of pattern theory is to create mathematical knowledge representations of complex systems, analyse the mathematical properties of the resulting regular structures, and to apply them to practically occuring patterns in nature and the man-made world. Starting from an algebraic formulation of such representations they are studied in terms of their topological, dynamical and probabilistic aspects. Patterns are expressed through their typical behaviour as well as through their variability around their typical form. Employing the representations (regular structures) algorithms are derived for the understanding, recognition, and restoration of observed patterns. The algorithms are investigated through computer experiments.
Markov Models For Pattern Recognition
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Author : Gernot A. Fink
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-14
Markov Models For Pattern Recognition written by Gernot A. Fink and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Computers categories.
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.
Distribution Theory Of Runs And Patterns And Its Applications
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Author : James C. Fu
language : en
Publisher: World Scientific
Release Date : 2003
Distribution Theory Of Runs And Patterns And Its Applications written by James C. Fu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
A rigorous, comprehensive introduction to the finite Markov chain imbedding technique for studying the distributions of runs and patterns from a unified and intuitive viewpoint, away from the lines of traditional combinatorics.
Syntactic And Structural Pattern Recognition
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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 1990
Syntactic And Structural Pattern Recognition written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.