The method of densities for non-isotropic Boolean models

The method of densities for non-isotropic Boolean models
Author: Hoerrmann, Julia
Publisher: KIT Scientific Publishing
Total Pages: 140
Release: 2015-03-20
Genre: Mathematics
ISBN: 3731503298

This book deals with the Boolean model, a basic model of stochastic geometry for the description of porous structures like the pore space in sand stone. The main result is a formula which gives in two and three dimensions a series representation of the most important model parameter, the intensity, using densities of so-called harmonic intrinsic volumes, which are new observable geometric quantities.

Tensor Valuations and Their Applications in Stochastic Geometry and Imaging

Tensor Valuations and Their Applications in Stochastic Geometry and Imaging
Author: Eva B. Vedel Jensen
Publisher: Springer
Total Pages: 469
Release: 2017-06-10
Genre: Mathematics
ISBN: 3319519514

The purpose of this volume is to give an up-to-date introduction to tensor valuations and their applications. Starting with classical results concerning scalar-valued valuations on the families of convex bodies and convex polytopes, it proceeds to the modern theory of tensor valuations. Product and Fourier-type transforms are introduced and various integral formulae are derived. New and well-known results are presented, together with generalizations in several directions, including extensions to the non-Euclidean setting and to non-convex sets. A variety of applications of tensor valuations to models in stochastic geometry, to local stereology and to imaging are also discussed.

Stochastic Geometry

Stochastic Geometry
Author: W. Weil
Publisher: Springer
Total Pages: 302
Release: 2006-10-26
Genre: Mathematics
ISBN: 3540381759

Stochastic Geometry is the mathematical discipline which studies mathematical models for random geometric structures. This book collects lectures presented at the CIME summer school in Martina Franca in September 2004. The main lecturers covered Spatial Statistics, Random Points, Integral Geometry and Random Sets. These are complemented by two additional contributions on Random Mosaics and Crystallization Processes. The book presents a comprehensive and up-to-date description of important aspects of Stochastic Geometry.

Statistical Physics and Spatial Statistics

Statistical Physics and Spatial Statistics
Author: Klaus R. Mecke
Publisher: Springer
Total Pages: 420
Release: 2008-01-11
Genre: Mathematics
ISBN: 3540450432

Modern physics is confronted with a large variety of complex spatial patterns. Although both spatial statisticians and statistical physicists study random geometrical structures, there has been only little interaction between the two up to now because of different traditions and languages. This volume aims to change this situation by presenting in a clear way fundamental concepts of spatial statistics which are of great potential value for condensed matter physics and materials sciences in general, and for porous media, percolation and Gibbs processes in particular. Geometric aspects, in particular ideas of stochastic and integral geometry, play a central role throughout. With nonspecialist researchers and graduate students also in mind, prominent physicists give an excellent introduction here to modern ideas of statistical physics pertinent to this exciting field of research.

Advances in Geophysics

Advances in Geophysics
Author: Ru-Shan Wu
Publisher: Elsevier
Total Pages: 627
Release: 2006-12-14
Genre: Science
ISBN: 0080466354

Significant progress in our understanding of the Earth's structure and functioning is dependent on new and original observations. However, these observations cannot be interpreted in a quantitative way without tools to model them, and developing adequate modelling methods is also a prerequisite for progress. Seismological raw data in the 21st century are mostly three-component broadband recordings, and require advanced numerical tools to be modelled, especially if lateral variations in the model are accounted for in addition to the radial stratification of the Earth. Considerable progress has been made concerning modelling of elastic waves in laterally heterogeneous structures in the last decades, taking advantage of the development of computer power. The number of articles related to new developments of diverse methods is enormous and it can be very difficult for newcomers to get an overview of the different methods available, and to be able to find which method is most appropriate for his or her applications. This book aims at giving introductions and basic reviews of the modelling methods for elastic waves in laterally heterogeneous structures which are most commonly used in contemporary seismology, or may have great potential for the future.

Stochastic and Integral Geometry

Stochastic and Integral Geometry
Author: Rolf Schneider
Publisher: Springer Science & Business Media
Total Pages: 692
Release: 2008-09-08
Genre: Mathematics
ISBN: 354078859X

Stochastic geometry deals with models for random geometric structures. Its early beginnings are found in playful geometric probability questions, and it has vigorously developed during recent decades, when an increasing number of real-world applications in various sciences required solid mathematical foundations. Integral geometry studies geometric mean values with respect to invariant measures and is, therefore, the appropriate tool for the investigation of random geometric structures that exhibit invariance under translations or motions. Stochastic and Integral Geometry provides the mathematically oriented reader with a rigorous and detailed introduction to the basic stationary models used in stochastic geometry – random sets, point processes, random mosaics – and to the integral geometry that is needed for their investigation. The interplay between both disciplines is demonstrated by various fundamental results. A chapter on selected problems about geometric probabilities and an outlook to non-stationary models are included, and much additional information is given in the section notes.

Lectures on the Poisson Process

Lectures on the Poisson Process
Author: Günter Last
Publisher: Cambridge University Press
Total Pages: 315
Release: 2017-10-26
Genre: Mathematics
ISBN: 1108505961

The Poisson process, a core object in modern probability, enjoys a richer theory than is sometimes appreciated. This volume develops the theory in the setting of a general abstract measure space, establishing basic results and properties as well as certain advanced topics in the stochastic analysis of the Poisson process. Also discussed are applications and related topics in stochastic geometry, including stationary point processes, the Boolean model, the Gilbert graph, stable allocations, and hyperplane processes. Comprehensive, rigorous, and self-contained, this text is ideal for graduate courses or for self-study, with a substantial number of exercises for each chapter. Mathematical prerequisites, mainly a sound knowledge of measure-theoretic probability, are kept in the background, but are reviewed comprehensively in the appendix. The authors are well-known researchers in probability theory; especially stochastic geometry. Their approach is informed both by their research and by their extensive experience in teaching at undergraduate and graduate levels.

Stochastic Geometry and Its Applications

Stochastic Geometry and Its Applications
Author: Sung Nok Chiu
Publisher: John Wiley & Sons
Total Pages: 561
Release: 2013-06-27
Genre: Mathematics
ISBN: 1118658256

An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital applications to spatial statistics and as a very interesting field of mathematics in its own right. This edition: Presents a wealth of models for spatial patterns and related statistical methods. Provides a great survey of the modern theory of random tessellations, including many new models that became tractable only in the last few years. Includes new sections on random networks and random graphs to review the recent ever growing interest in these areas. Provides an excellent introduction to theory and modelling of point processes, which covers some very latest developments. Illustrate the forefront theory of random sets, with many applications. Adds new results to the discussion of fibre and surface processes. Offers an updated collection of useful stereological methods. Includes 700 new references. Is written in an accessible style enabling non-mathematicians to benefit from this book. Provides a companion website hosting information on recent developments in the field www.wiley.com/go/cskm Stochastic Geometry and its Applications is ideally suited for researchers in physics, materials science, biology and ecological sciences as well as mathematicians and statisticians. It should also serve as a valuable introduction to the subject for students of mathematics and statistics.

Space, Structure and Randomness

Space, Structure and Randomness
Author: Michel Bilodeau
Publisher: Springer Science & Business Media
Total Pages: 402
Release: 2007-12-23
Genre: Mathematics
ISBN: 0387291156

Space, structure, and randomness: these are the three key concepts underlying Georges Matheron’s scientific work. He first encountered them at the beginning of his career when working as a mining engineer, and then they resurfaced in fields ranging from meteorology to microscopy. What could these radically different types of applications possibly have in common? First, in each one only a single realisation of the phenomenon is available for study, but its features repeat themselves in space; second, the sampling pattern is rarely regular, and finally there are problems of change of scale. This volume is divided in three sections on random sets, geostatistics and mathematical morphology. They reflect his professional interests and his search for underlying unity. Some readers may be surprised to find theoretical chapters mixed with applied ones. We have done this deliberately. GM always considered that the distinction between the theory and practice was purely academic. When GM tackled practical problems, he used his skill as a physicist to extract the salient features and to select variables which could be measured meaningfully and whose values could be estimated from the available data. Then he used his outstanding ability as a mathematician to solve the problems neatly and efficiently. It was his capacity to combine a physicist’s intuition with a mathematician’s analytical skills that allowed him to produce new and innovative solutions to difficult problems. The book should appeal to graduate students and researchers working in mathematics, probability, statistics, physics, spatial data analysis, and image analysis. In addition it will be of interest to those who enjoy discovering links between scientific disciplines that seem unrelated at first glance. In writing the book the contributors have tried to put GM’s ideas into perspective. During his working life, GM was a genuinely creative scientist. He developed innovative concepts whose usefulness goes far beyond the confines of the discipline for which they were originally designed. This is why his work remains as pertinent today as it was when it was first written.

Geostatistics Wollongong &96. 1 (1997)

Geostatistics Wollongong &96. 1 (1997)
Author: Ernest Y. Baafi
Publisher: Springer Science & Business Media
Total Pages: 792
Release: 1997
Genre: Science
ISBN: 9780792344940

The papers in this volume provide a comprehensive account of the current methods and work in geostatistics, including recent theoretical developments and applications. Topics featured include: stochastic simulations, space-time modelling, and Bayesian framework.