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Saturday, May 9, 2020 | History

2 edition of Random sets and integral geometry found in the catalog.

Random sets and integral geometry

G. Matheron

Random sets and integral geometry

by G. Matheron

  • 180 Want to read
  • 3 Currently reading

Published in New York, Toronto :bWiley .
Written in English

    Subjects:
  • Geometric probabilities.,
  • Integral geometry.,
  • Set theory.

  • Edition Notes

    Includes bibliographical references and index.

    StatementG. Matheron.
    SeriesWiley series in probability and mathematical statistics
    Classifications
    LC ClassificationsQA273.5 M37
    The Physical Object
    Paginationxxiii, 261 p. ;
    Number of Pages261
    ID Numbers
    Open LibraryOL18802676M

      A new definition of random sets is proposed. Random Sets a nd Integral Geometry. Jo hn. Wiley & Sons This book has been written on the base of my lectures at the Department of Probability. This chapter discusses integral geometry. Integral geometry is concerned with the study, computation, and application of invariant measures on sets of geometric objects. It has its roots in some questions on geometric probabilities. Integral geometry is closely connected to the geometry of convex bodies.

    Integral Geometry a branch of mathematics that studies certain special numerical characteristics (“measures”) for sets of points, lines, planes, and other geometrical objects, calculated, as a rule, with the aid of integration. Here the “measure” must satisfy the following two requirements: (1) additivity (the measure of a set consisting of. Integral geometry originated with problems on geometrical probability and convex bodies. Its later developments, however, have proved to be useful in several fields ranging from pure mathematics (measure theory, continuous groups) to technical and Cited by:

    Although random sets have been around for sometime and appeared in many areas such as stochastic geometry, a solid theory of random sets on locally compact, Hausdorff, second countable spaces appeared only in with Matheron’s book [9].Cited by: Molchanov I. Theory of Random Sets. The book will be an invaluable reference for probabilists, mathematicians in convex and integral geometry, set-valued analysis, capacity and potential theory, mathematical statisticians in spatial statistics and image analysis, specialists in mathematical economics, and electronic and electrical engineers.


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Random sets and integral geometry by G. Matheron Download PDF EPUB FB2

Random sets and integral geometry. [Georges Matheron] Home. WorldCat Home About WorldCat Help. Search. Search for Library Items Search for Lists Search for Contacts Search for a Library. Create Book\/a>, schema:CreativeWork\/a> ; \u00A0\u00A0\u00A0\n library.

Additional Physical Format: Online version: Matheron, G. (Georges). Random sets and integral geometry. New York ; London: Wiley, (OCoLC) Random sets and integral geometry (Wiley series in probability and mathematical statistics) Hardcover – January 1, by G Matheron (Author) › Visit Amazon's G Matheron Page.

Find all the books, read about the author, and more. Author: G Matheron. where is a set of points in the parameter space of the Lie group and is an integral invariant of the group, defined by equation (1), or the density measure.

The integral in (2) is also called an elementary measure of the set of manifolds. A specific choice of this measure sets up a complete correspondence with the fundamental problem in the study of geometric probabilities. Random Sets and Integral Geometry (Probability & Mathematical Statistics) By Matheron, F.

To download Random Sets and Integral Geometry (Probability & Mathematical Statistics) eBook, make sure you follow the web link under and download the document or get access to other information which are relevant to RANDOM SETS AND INTEGRAL GEOMETRY.

Random sets and integral geometry. Georges Matheron. Wiley, - Mathematics - pages. 0 Reviews. From inside the book. What people are saying - Write a review.

We haven't found any reviews in the usual places. Mathematics / Geometry / General Mathematics / Probability & Statistics / General Mathematics / Set Theory Probabilities.

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 Cited by: This book, by two eminent specialists of the subject, provides a solid mathematical treatment of the basic models of stochastic geometry -- random sets, point processes of geometric objects (particles, flats), and random mosaics.

What I do know is that there’s a book called Geometric Tomography by Richard Gardner that’s used as a reference for pure integral geometry.

Tomography and stereology both seem to be words for the science of medical scanning. (Question 2 should make the connection with integral geometry plausible: lines being fired through a body).

Buy Random Sets and Integral Geometry by G Matheron online at Alibris. We have new and used copies available, in 1 editions - starting at $ Shop Range: $ - $ "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. Stochastic Geometry is the mathematical discipline which studies mathematical models for random geometric structures, as they appear frequently in almost all natural sciences or technical fields.

Although its roots can be traced back to the 18th century (the Buffon needle problem), the modern theory of random sets was founded by D. Kendall and G. Matheron in. In mathematics, a random compact set is essentially a compact set-valued random compact sets are useful in the study of attractors for random dynamical systems.

Definition. Let (,) be a complete separable metric denote the set of all compact subsets Hausdorff metric on is defined by (,):= {∈ ∈ (,), ∈ ∈ (,)}.(,) is also. Integral geometry – measure theoretic approach and stochastic applications Rolf Schneider Preface Integral geometry, as it is understood here, deals with the computation and appFile Size: KB.

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 new references. Is written in an accessible style enabling non-mathematicians to benefit from this book. Random sets and integral geometry. New York: Wiley. MLA Citation. Matheron, G. Random sets and integral geometry [by] G.

Matheron Wiley New York Australian/Harvard Citation. Matheron, G.Random sets and integral geometry [by] G. Matheron Wiley New York.

Wikipedia Citation. In mathematics, stochastic geometry is the study of random spatial patterns. At the heart of the subject lies the study of random point patterns.

This leads to the theory of spatial point processes, hence notions of Palm conditioning, which extend to. The book is divided into five main chapters: Random Closed Sets and Capacity Functionals, Expectations of Random Sets, Minkowski Addition, Unions of Random Sets, and Random Sets and Random Functions.

Each of the five chapters represents important concepts in the theory of random sets. The capacity functional is explained in first chapter. Integral Geometry. Second Example. Theorem (Firey’s Colliding Dice Problem []) Suppose Ω 1 and Ω 2 are disjoint unit cubes in R3.

In a random collision, the probablity that the cubes collide edge-to-edge slightly exceeds the probability that the cubes collide corner-to-face. Indeed,File Size: KB. Theory of Random Sets presents a state of the art treatment of the modern theory, but it does not neglect to recall and build on the foundations laid by Matheron and others, including the vast advances in stochastic geometry, probability theory, set.

Kinematic Formula and the integral geometry of random sets Jonathan Taylor Stanford University Proof: Poincar e’s limit Model process For M ˆS(Rj) de ne a Rk valued process fn(t;g n) = ˇ k(n1=2g nt) where g n 2O(n)is a Haar-distributed random matrix and ˇ k: S n1=2(R n)!Rk is projection onto the rst k coordinates.Part II: Integral Geometry.- ing with Invariant Measures.- ed Concepts of Integral Geometry.- al-geometric Transformations.- Part III: Selected Topics from Stochastic Geometry.- Geometric Probability Problems.- Values for Random Sets.- Random Mosaics.- Non-stationary Models  Essentials of integral geometry in a homogenous space are presented and the focus is on the basic results and applications.

This book provides the readers with new findings, some being published for the first time and serves as an excellent graduate text. Request Inspection Copy. Contents: Basic Properties of Convex Sets.