Stochastic Geometry : Modern Research Frontiers

David Coupier

ISBN 10: 3030135462 / ISBN 13: 9783030135461

Published by Springer, Palgrave Macmillan, 2019

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures.The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject: understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes.Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications.

Seller Inventory # 9783030135461

Bibliographic Details

• Title: Stochastic Geometry : Modern Research Frontiers
• Publisher: Springer, Palgrave Macmillan
• Publication Date: 2019
• Language: English
• ISBN 10: 3030135462
• ISBN 13: 9783030135461
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 14D millimeters 235 millimeters width by 155 millimeters height by 14 millimeters depth
• Weight: 382 grams

About this title

Synopsis

This volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. 

Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures.

The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject:  understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes.

Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications.