Random Fields and Geometry

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Publisher : Springer Science & Business Media
ISBN 13 : 0387481168
Total Pages : 455 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Random Fields and Geometry by : R. J. Adler

Download or read book Random Fields and Geometry written by R. J. Adler and published by Springer Science & Business Media. This book was released on 2009-01-29 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is devoted to a completely new approach to geometric problems arising in the study of random fields. The groundbreaking material in Part III, for which the background is carefully prepared in Parts I and II, is of both theoretical and practical importance, and striking in the way in which problems arising in geometry and probability are beautifully intertwined. "Random Fields and Geometry" will be useful for probabilists and statisticians, and for theoretical and applied mathematicians who wish to learn about new relationships between geometry and probability. It will be helpful for graduate students in a classroom setting, or for self-study. Finally, this text will serve as a basic reference for all those interested in the companion volume of the applications of the theory.

The Geometry of Random Fields

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Publisher : SIAM
ISBN 13 : 0898716934
Total Pages : 295 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis The Geometry of Random Fields by : Robert J. Adler

Download or read book The Geometry of Random Fields written by Robert J. Adler and published by SIAM. This book was released on 2010-01-28 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important treatment of the geometric properties of sets generated by random fields, including a comprehensive treatment of the mathematical basics of random fields in general. It is a standard reference for all researchers with an interest in random fields, whether they be theoreticians or come from applied areas.

Gaussian Markov Random Fields

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Publisher : CRC Press
ISBN 13 : 0203492021
Total Pages : 280 pages
Book Rating : 4.2/5 (34 download)

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Book Synopsis Gaussian Markov Random Fields by : Havard Rue

Download or read book Gaussian Markov Random Fields written by Havard Rue and published by CRC Press. This book was released on 2005-02-18 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studie

Markov Random Fields

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Publisher : Springer Science & Business Media
ISBN 13 : 1461381908
Total Pages : 207 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Markov Random Fields by : Y.A. Rozanov

Download or read book Markov Random Fields written by Y.A. Rozanov and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we study Markov random functions of several variables. What is traditionally meant by the Markov property for a random process (a random function of one time variable) is connected to the concept of the phase state of the process and refers to the independence of the behavior of the process in the future from its behavior in the past, given knowledge of its state at the present moment. Extension to a generalized random process immediately raises nontrivial questions about the definition of a suitable" phase state," so that given the state, future behavior does not depend on past behavior. Attempts to translate the Markov property to random functions of multi-dimensional "time," where the role of "past" and "future" are taken by arbitrary complementary regions in an appro priate multi-dimensional time domain have, until comparatively recently, been carried out only in the framework of isolated examples. How the Markov property should be formulated for generalized random functions of several variables is the principal question in this book. We think that it has been substantially answered by recent results establishing the Markov property for a whole collection of different classes of random functions. These results are interesting for their applications as well as for the theory. In establishing them, we found it useful to introduce a general probability model which we have called a random field. In this book we investigate random fields on continuous time domains. Contents CHAPTER 1 General Facts About Probability Distributions §1.

Microstructural Randomness and Scaling in Mechanics of Materials

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Publisher : CRC Press
ISBN 13 : 1420010271
Total Pages : 500 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Microstructural Randomness and Scaling in Mechanics of Materials by : Martin Ostoja-Starzewski

Download or read book Microstructural Randomness and Scaling in Mechanics of Materials written by Martin Ostoja-Starzewski and published by CRC Press. This book was released on 2007-08-13 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: An area at the intersection of solid mechanics, materials science, and stochastic mathematics, mechanics of materials often necessitates a stochastic approach to grasp the effects of spatial randomness. Using this approach, Microstructural Randomness and Scaling in Mechanics of Materials explores numerous stochastic models and methods used in the m

Markov Random Fields for Vision and Image Processing

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Publisher : MIT Press
ISBN 13 : 0262015773
Total Pages : 472 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Markov Random Fields for Vision and Image Processing by : Andrew Blake

Download or read book Markov Random Fields for Vision and Image Processing written by Andrew Blake and published by MIT Press. This book was released on 2011-07-22 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study. This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications. After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools.

Stationary Sequences and Random Fields

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Publisher : Springer Science & Business Media
ISBN 13 : 1461251567
Total Pages : 253 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Stationary Sequences and Random Fields by : Murray Rosenblatt

Download or read book Stationary Sequences and Random Fields written by Murray Rosenblatt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a dual purpose. One of these is to present material which selec tively will be appropriate for a quarter or semester course in time series analysis and which will cover both the finite parameter and spectral approach. The second object is the presentation of topics of current research interest and some open questions. I mention these now. In particular, there is a discussion in Chapter III of the types of limit theorems that will imply asymptotic nor mality for covariance estimates and smoothings of the periodogram. This dis cussion allows one to get results on the asymptotic distribution of finite para meter estimates that are broader than those usually given in the literature in Chapter IV. A derivation of the asymptotic distribution for spectral (second order) estimates is given under an assumption of strong mixing in Chapter V. A discussion of higher order cumulant spectra and their large sample properties under appropriate moment conditions follows in Chapter VI. Probability density, conditional probability density and regression estimates are considered in Chapter VII under conditions of short range dependence. Chapter VIII deals with a number of topics. At first estimates for the structure function of a large class of non-Gaussian linear processes are constructed. One can determine much more about this structure or transfer function in the non-Gaussian case than one can for Gaussian processes. In particular, one can determine almost all the phase information.

Random Fields and Spin Glasses

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Publisher : Cambridge University Press
ISBN 13 : 9780521847834
Total Pages : 240 pages
Book Rating : 4.8/5 (478 download)

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Book Synopsis Random Fields and Spin Glasses by : Cirano De Dominicis

Download or read book Random Fields and Spin Glasses written by Cirano De Dominicis and published by Cambridge University Press. This book was released on 2006-10-26 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces some useful and little known techniques in statistical mechanics and field theory including multiple Legendre transforms, supersymmetry, Fourier transforms on a tree, infinitesimal permutations and Ward Takahashi Identities."--Jacket.

Multiparameter Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 0387216316
Total Pages : 590 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Multiparameter Processes by : Davar Khoshnevisan

Download or read book Multiparameter Processes written by Davar Khoshnevisan and published by Springer Science & Business Media. This book was released on 2006-04-10 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-contained presentation: from elementary material to state-of-the-art research; Much of the theory in book-form for the first time; Connections are made between probability and other areas of mathematics, engineering and mathematical physics

Random Fields for Spatial Data Modeling

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Publisher : Springer Nature
ISBN 13 : 9402419187
Total Pages : 884 pages
Book Rating : 4.4/5 (24 download)

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Book Synopsis Random Fields for Spatial Data Modeling by : Dionissios T. Hristopulos

Download or read book Random Fields for Spatial Data Modeling written by Dionissios T. Hristopulos and published by Springer Nature. This book was released on 2020-02-17 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spatial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means of models based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author’s research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatial data analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.

Spatiotemporal Random Fields

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Publisher : Elsevier
ISBN 13 : 0128030321
Total Pages : 698 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Spatiotemporal Random Fields by : George Christakos

Download or read book Spatiotemporal Random Fields written by George Christakos and published by Elsevier. This book was released on 2017-07-26 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatiotemporal Random Fields: Theory and Applications, Second Edition, provides readers with a new and updated edition of the text that explores the application of spatiotemporal random field models to problems in ocean, earth, and atmospheric sciences, spatiotemporal statistics, and geostatistics, among others. The new edition features considerable detail of spatiotemporal random field theory, including ordinary and generalized models, as well as space-time homostationary, isostationary and hetrogeneous approaches. Presenting new theoretical and applied results, with particular emphasis on space-time determination and interpretation, spatiotemporal analysis and modeling, random field geometry, random functionals, probability law, and covariance construction techniques, this book highlights the key role of space-time metrics, the physical interpretation of stochastic differential equations, higher-order space-time variability functions, the validity of major theoretical assumptions in real-world practice (covariance positive-definiteness, metric-adequacy etc.), and the emergence of interdisciplinary phenomena in conditions of multi-sourced real-world uncertainty. Contains applications in the form of examples and case studies, providing readers with first-hand experiences Presents an easy to follow narrative which progresses from simple concepts to more challenging ideas Includes significant updates from the previous edition, including a focus on new theoretical and applied results

Markov Random Field Modeling in Image Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1848002793
Total Pages : 372 pages
Book Rating : 4.8/5 (48 download)

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Book Synopsis Markov Random Field Modeling in Image Analysis by : Stan Z. Li

Download or read book Markov Random Field Modeling in Image Analysis written by Stan Z. Li and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; Learning MRF for Classification. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas.

Spin Glasses and Random Fields

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Publisher : World Scientific
ISBN 13 : 9810232403
Total Pages : 454 pages
Book Rating : 4.8/5 (12 download)

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Book Synopsis Spin Glasses and Random Fields by : A. Peter Young

Download or read book Spin Glasses and Random Fields written by A. Peter Young and published by World Scientific. This book was released on 1998 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last few years have seen many developments in the study of ?frustrated? systems, such as spin glasses and random fields. In addition, the application of the idea of spin glasses to other branches of physics, such as vortex lines in high temperature superconductors, protein folding, structural glasses, and the vulcanization of rubber, has been flourishing. The earlier reviews are several years old, so now is an appropriate time to summarize the recent developments. The articles in this book have been written by leading researchers and include theoretical and experimental studies, and large-scale numerical work (using state-of-the-art algorithms designed specifically for spin-glass-type problems), as well as analytical studies.

Random Fields

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Publisher : World Scientific
ISBN 13 : 9812563539
Total Pages : 363 pages
Book Rating : 4.8/5 (125 download)

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Book Synopsis Random Fields by : Erik Vanmarcke

Download or read book Random Fields written by Erik Vanmarcke and published by World Scientific. This book was released on 2010 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random variation is a fact of life that provides substance to a wide range of problems in the sciences, engineering, and economics. There is a growing need in diverse disciplines to model complex patterns of variation and interdependence using random fields, as both deterministic treatment and conventional statistics are often insufficient. An ideal random field model will capture key features of complex random phenomena in terms of a minimum number of physically meaningful and experimentally accessible parameters. This volume, a revised and expanded edition of an acclaimed book first published by the M I T Press, offers a synthesis of methods to describe and analyze and, where appropriate, predict and control random fields. There is much new material, covering both theory and applications, notably on a class of probability distributions derived from quantum mechanics, relevant to stochastic modeling in fields such as cosmology, biology and system reliability, and on discrete-unit or agent-based random processes.Random Fields is self-contained and unified in presentation. The first edition was found, in a review in EOS (American Geophysical Union) to be ?both technically interesting and a pleasure to read ? the presentation is clear and the book should be useful to almost anyone who uses random processes to solve problems in engineering or science ? and (there is) continued emphasis on describing the mathematics in physical terms.?

Image Textures and Gibbs Random Fields

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Publisher : Springer Science & Business Media
ISBN 13 : 9780792359616
Total Pages : 274 pages
Book Rating : 4.3/5 (596 download)

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Book Synopsis Image Textures and Gibbs Random Fields by : Georgiĭ Lʹvovich Gimelʹfarb

Download or read book Image Textures and Gibbs Random Fields written by Georgiĭ Lʹvovich Gimelʹfarb and published by Springer Science & Business Media. This book was released on 1999 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents techniques for describing image textures. Contrary to the usual practice of embedding the images to known modelling frameworks borrowed from statistical physics or other domains, this book deduces the Gibbs models from basic image features and tailors the modelling framework to the images. This approach results in more general Gibbs models than can be either Markovian or non-Markovian and possess arbitrary interaction structures and strengths. The book presents computationally feasible algorithms for parameter estimation and image simulation and demonstrates their abilities and limitations by numerous experimental results.

An Introduction to Conditional Random Fields

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Publisher : Now Pub
ISBN 13 : 9781601985729
Total Pages : 120 pages
Book Rating : 4.9/5 (857 download)

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Book Synopsis An Introduction to Conditional Random Fields by : Charles Sutton

Download or read book An Introduction to Conditional Random Fields written by Charles Sutton and published by Now Pub. This book was released on 2012 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Conditional Random Fields provides a comprehensive tutorial aimed at application-oriented practitioners seeking to apply CRFs. The monograph does not assume previous knowledge of graphical modeling, and so is intended to be useful to practitioners in a wide variety of fields.

Gaussian and Non-Gaussian Linear Time Series and Random Fields

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Publisher : Springer Science & Business Media
ISBN 13 : 9780387989174
Total Pages : 272 pages
Book Rating : 4.9/5 (891 download)

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Book Synopsis Gaussian and Non-Gaussian Linear Time Series and Random Fields by : Murray Rosenblatt

Download or read book Gaussian and Non-Gaussian Linear Time Series and Random Fields written by Murray Rosenblatt and published by Springer Science & Business Media. This book was released on 2000 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.