LEADER 03507nam 22006135 450 001 996466649603316 005 20200705154250.0 010 $a3-030-13547-0 024 7 $a10.1007/978-3-030-13547-8 035 $a(CKB)4100000007881291 035 $a(DE-He213)978-3-030-13547-8 035 $a(MiAaPQ)EBC5922969 035 $a(PPN)235668257 035 $a(EXLCZ)994100000007881291 100 $a20190409d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStochastic Geometry$b[electronic resource] $eModern Research Frontiers /$fedited by David Coupier 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XIII, 232 p. 71 illus., 27 illus. in color.) 225 1 $aLecture Notes in Mathematics,$x0075-8434 ;$v2237 311 $a3-030-13546-2 320 $aIncludes bibliographical references. 330 $aThis volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures. The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject: understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes. Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications. . 410 0$aLecture Notes in Mathematics,$x0075-8434 ;$v2237 606 $aProbabilities 606 $aStatistics  606 $aOptical data processing 606 $aMathematical physics 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aMathematical Applications in the Physical Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/M13120 615 0$aProbabilities. 615 0$aStatistics . 615 0$aOptical data processing. 615 0$aMathematical physics. 615 14$aProbability Theory and Stochastic Processes. 615 24$aStatistical Theory and Methods. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aMathematical Applications in the Physical Sciences. 676 $a519.2 702 $aCoupier$b David$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466649603316 996 $aStochastic geometry$960031 997 $aUNISA