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Author : Sanjoy K. Mitter
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.:/5 (368 download)
Download or read book Modelling and Estimation for Random Fields written by Sanjoy K. Mitter and published by . This book was released on 1992 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dionissios T. Hristopulos
Publisher : Springer Nature
ISBN 13 : 9402419187
Total Pages : 884 pages
Book Rating : 4.4/5 (24 download)
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.
Author : Stan Z. Li
Publisher : Springer Science & Business Media
ISBN 13 : 1848002793
Total Pages : 372 pages
Book Rating : 4.8/5 (48 download)
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.
Author : Xavier Guyon
Publisher : Springer Science & Business Media
ISBN 13 : 9780387944289
Total Pages : 294 pages
Book Rating : 4.9/5 (442 download)
Download or read book Random Fields on a Network written by Xavier Guyon and published by Springer Science & Business Media. This book was released on 1995-06-23 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory of spatial models over lattices, or random fields as they are known, has developed significantly over recent years. This book provides a graduate-level introduction to the subject which assumes only a basic knowledge of probability and statistics, finite Markov chains, and the spectral theory of second-order processes. A particular strength of this book is its emphasis on examples - both to motivate the theory which is being developed, and to demonstrate the applications which range from statistical mechanics to image analysis and from statistics to stochastic algorithms.
Author : S.Z. Li
Publisher : Springer Science & Business Media
ISBN 13 : 4431669337
Total Pages : 274 pages
Book Rating : 4.4/5 (316 download)
Download or read book Markov Random Field Modeling in Computer Vision written by S.Z. Li and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov random field (MRF) modeling provides a basis for the characterization of contextual constraints on visual interpretation and enables us to develop optimal vision algorithms systematically based on sound principles. This book presents a comprehensive study on using MRFs to solve computer vision problems, covering the following parts essential to the subject: introduction to fundamental theories, formulations of various vision models in the MRF framework, MRF parameter estimation, and optimization algorithms. Various MRF vision models are presented in a unified form, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This book is an excellent reference for researchers working in computer vision, image processing, pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in the subject.
Author : George Christakos
Publisher : Elsevier
ISBN 13 : 1483288307
Total Pages : 503 pages
Book Rating : 4.4/5 (832 download)
Download or read book Random Field Models in Earth Sciences written by George Christakos and published by Elsevier. This book was released on 2013-10-22 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about modeling as a prinicipal component of scientific investigations. In general terms, modeling is the funamental process of combining intellectual creativity with physical knowledge and mathematical techniques in order to learn the properties of the mechanisms underlying a physical phenomenon and make predictions. The book focuses on a specific class of models, namely, random field models and certain of their physical applications in the context of a stochastic data analysis and processing research program. The term application is considered here in the sense wherein the mathematical random field model is shaping, but is also being shaped by, its objects. This book explores the application of random field models and stochastic data processing to problems in hydrogeology, geostatistics, climate modeling, and oil reservoir engineering, among others Researchers in the geosciences who work with models of natural processes will find discussion of; Spatiotemporal random fields Space transformation Multidimensional estimation Simulation Sampling design Stochastic partial differential equations
Author : Alexander G. Ramm
Publisher : World Scientific
ISBN 13 : 9812565361
Total Pages : 390 pages
Book Rating : 4.8/5 (125 download)
Download or read book Random Fields Estimation written by Alexander G. Ramm and published by World Scientific. This book was released on 2005 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a novel theory of random fields estimation of Wiener type, developed originally by the author and presented here. No assumption about the Gaussian or Markovian nature of the fields are made. The theory, constructed entirely within the framework of covariance theory, is based on a detailed analytical study of a new class of multidimensional integral equations basic in estimation theory.This book is suitable for graduate courses in random fields estimation. It can also be used in courses in functional analysis, numerical analysis, integral equations, and scattering theory.
Author : Barbara Bajusz Lawton
Publisher :
ISBN 13 :
Total Pages : 362 pages
Book Rating : 4.:/5 (18 download)
Download or read book Mixtures of Random Fields written by Barbara Bajusz Lawton and published by . This book was released on 1985 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : George Christakos
Publisher : Courier Corporation
ISBN 13 : 0486160912
Total Pages : 514 pages
Book Rating : 4.4/5 (861 download)
Download or read book Random Field Models in Earth Sciences written by George Christakos and published by Courier Corporation. This book was released on 2012-08-09 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text for graduate students examines problems related to earth and environmental sciences by means of theoretical models based on a purely random (stochastic) element. 103 figures. 16 tables.
Author : Tobias Kegel
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (796 download)
Download or read book Simulation and Estimation of Operator Scaling Stable Random Fields written by Tobias Kegel and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Antonino Freno
Publisher : Springer Science & Business Media
ISBN 13 : 3642203086
Total Pages : 217 pages
Book Rating : 4.6/5 (422 download)
Download or read book Hybrid Random Fields written by Antonino Freno and published by Springer Science & Business Media. This book was released on 2011-04-11 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an exciting new synthesis of directed and undirected, discrete and continuous graphical models. Combining elements of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these worlds, with an added promise of modularity and scalability. The authors have written an enjoyable book---rigorous in the treatment of the mathematical background, but also enlivened by interesting and original historical and philosophical perspectives. -- Manfred Jaeger, Aalborg Universitet The book not only marks an effective direction of investigation with significant experimental advances, but it is also---and perhaps primarily---a guide for the reader through an original trip in the space of probabilistic modeling. While digesting the book, one is enriched with a very open view of the field, with full of stimulating connections. [...] Everyone specifically interested in Bayesian networks and Markov random fields should not miss it. -- Marco Gori, Università degli Studi di Siena Graphical models are sometimes regarded---incorrectly---as an impractical approach to machine learning, assuming that they only work well for low-dimensional applications and discrete-valued domains. While guiding the reader through the major achievements of this research area in a technically detailed yet accessible way, the book is concerned with the presentation and thorough (mathematical and experimental) investigation of a novel paradigm for probabilistic graphical modeling, the hybrid random field. This model subsumes and extends both Bayesian networks and Markov random fields. Moreover, it comes with well-defined learning algorithms, both for discrete and continuous-valued domains, which fit the needs of real-world applications involving large-scale, high-dimensional data.
Author : Rama Chellappa
Publisher :
ISBN 13 :
Total Pages : 608 pages
Book Rating : 4.3/5 (91 download)
Download or read book Markov Random Fields written by Rama Chellappa and published by . This book was released on 1993 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the theory and application of Markov random fields in image processing/computer vision. Modelling images through the local interaction of Markov models produces algorithms for use in texture analysis, image synthesis, restoration, segmentation and surface reconstruction.
Author : Charles Sutton
Publisher :
ISBN 13 : 9781601985736
Total Pages : 119 pages
Book Rating : 4.9/5 (857 download)
Download or read book An Introduction to Conditional Random Fields written by Charles Sutton and published by . This book was released on 2012 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many tasks involve predicting a large number of variables that depend on each other as well as on other observed variables. Structured prediction methods are essentially a combination of classification and graphical modeling. They combine the ability of graphical models to compactly model multivariate data with the ability of classification methods to perform prediction using large sets of input features. This survey describes conditional random fields, a popular probabilistic method for structured prediction. CRFs have seen wide application in many areas, including natural language processing, computer vision, and bioinformatics. We describe methods for inference and parameter estimation for CRFs, including practical issues for implementing large-scale CRFs. We do not assume previous knowledge of graphical modeling, so this survey is intended to be useful to practitioners in a wide variety of fields.
Author : CALIFORNIA UNIV DAVIS.
Publisher :
ISBN 13 :
Total Pages : 4 pages
Book Rating : 4.:/5 (227 download)
Download or read book Modeling and Estimation of Reciprocal Diffusion and Gauss-Markov Random Fields written by CALIFORNIA UNIV DAVIS. and published by . This book was released on 1992 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic goal of this research was to develop a theory of second order stochastic differential equations as a class of model for problems of filtering and estimation. This goal has been achieved for both continuous and discrete time linear-Gaussian reciprocal processes.
Author : Werner G. Müller
Publisher : Springer Science & Business Media
ISBN 13 : 3540311750
Total Pages : 250 pages
Book Rating : 4.5/5 (43 download)
Download or read book Collecting Spatial Data written by Werner G. Müller and published by Springer Science & Business Media. This book was released on 2007-08-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. Special attention is devoted to describing new methodologies to cope with the problem of correlated observations.
Author : Charles Sutton
Publisher : Now Pub
ISBN 13 : 9781601985729
Total Pages : 120 pages
Book Rating : 4.9/5 (857 download)
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.
Author : Priya Kohli
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (819 download)
Download or read book Prediction and Estimation of Random Fields written by Priya Kohli and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: For a stationary two dimensional random field, we utilize the classical Kolmogorov-Wiener theory to develop prediction methodology which requires minimal assumptions on the dependence structure of the random field. We also provide solutions for several non-standard prediction problems which deals with the "modified past," in which a finite number of observations are added to the past. These non-standard prediction problems are motivated by the network site selection in the environmental and geostatistical applications. Unlike the time series situation, the prediction results for random fields seem to be expressible only in terms of the moving average parameters, and attempts to express them in terms of the autoregressive parameters lead to a new and mysterious projection operator which captures the nature of edge-effects. We put forward an approach for estimating the predictor coefficients by carrying out an extension of the exponential models. Through simulation studies and real data example, we demonstrate the impressive performance of our prediction method. To the best of our knowledge, the proposed method is the first to deliver a unified framework for forecasting random fields both in the time and spectral domain without making a subjective choice of the covariance structure. Finally, we focus on the estimation of the hurst parameter for long range dependence stationary random fields, which draws its motivation from applications in the environmental and atmospheric processes. Current methods for estimation of the Hurst parameter include parametric models like fractional autoregressive integrated moving average models, and semiparametric estimators which are either inefficient or inconsistent. We propose a novel semiparametric estimator based on the fractional exponential spectrum. We develop three data-driven methods which can automatically select the optimal model order for the fractional exponential models. Extensive simulation studies and analysis of Mercer and Hall?s wheat data are used to illustrate the performance of the proposed estimator and model order selection criteria. The results show that our estimator outperforms existing estimators, including the GPH (Geweke and Porter-Hudak) estimator. We show that the proposed estimator is consistent, works for different definitions of long range dependent random fields, is computationally simple and is not susceptible to model misspecification or poor efficiency.
