Stochastic Geometric Analysis With Applications

Stochastic Geometric Analysis With Applications

Author: Ovidiu Calin

Publisher: World Scientific

Published: 2023-11-21

Total Pages: 557

ISBN-13: 981128329X

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This book is a comprehensive exploration of the interplay between Stochastic Analysis, Geometry, and Partial Differential Equations (PDEs). It aims to investigate the influence of geometry on diffusions induced by underlying structures, such as Riemannian or sub-Riemannian geometries, and examine the implications for solving problems in PDEs, mathematical finance, and related fields. The book aims to unify the relationships between PDEs, nonholonomic geometry, and stochastic processes, focusing on a specific condition shared by these areas known as the bracket-generating condition or Hörmander's condition. The main objectives of the book are:The intended audience for this book includes researchers and practitioners in mathematics, physics, and engineering, who are interested in stochastic techniques applied to geometry and PDEs, as well as their applications in mathematical finance and electrical circuits.


Book Synopsis Stochastic Geometric Analysis With Applications by : Ovidiu Calin

Download or read book Stochastic Geometric Analysis With Applications written by Ovidiu Calin and published by World Scientific. This book was released on 2023-11-21 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive exploration of the interplay between Stochastic Analysis, Geometry, and Partial Differential Equations (PDEs). It aims to investigate the influence of geometry on diffusions induced by underlying structures, such as Riemannian or sub-Riemannian geometries, and examine the implications for solving problems in PDEs, mathematical finance, and related fields. The book aims to unify the relationships between PDEs, nonholonomic geometry, and stochastic processes, focusing on a specific condition shared by these areas known as the bracket-generating condition or Hörmander's condition. The main objectives of the book are:The intended audience for this book includes researchers and practitioners in mathematics, physics, and engineering, who are interested in stochastic techniques applied to geometry and PDEs, as well as their applications in mathematical finance and electrical circuits.

Stochastic and Integral Geometry

Stochastic and Integral Geometry

Author: Rolf Schneider

Publisher: Springer Science & Business Media

Published: 2008-09-08

Total Pages: 692

ISBN-13: 354078859X

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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.


Book Synopsis Stochastic and Integral Geometry by : Rolf Schneider

Download or read book Stochastic and Integral Geometry written by Rolf Schneider and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Geometry

Stochastic Geometry

Author: Wilfrid S. Kendall

Publisher: Routledge

Published: 2019-06-10

Total Pages: 419

ISBN-13: 1351413724

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Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including: o a "crash-course" introduction to key stochastic geometry themes o considerations of geometric sampling bias issues o tesselations o shape o random sets o image analysis o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo


Book Synopsis Stochastic Geometry by : Wilfrid S. Kendall

Download or read book Stochastic Geometry written by Wilfrid S. Kendall and published by Routledge. This book was released on 2019-06-10 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including: o a "crash-course" introduction to key stochastic geometry themes o considerations of geometric sampling bias issues o tesselations o shape o random sets o image analysis o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo

Stochastic Geometry

Stochastic Geometry

Author: David Coupier

Publisher: Springer

Published: 2019-04-09

Total Pages: 232

ISBN-13: 3030135470

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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.


Book Synopsis Stochastic Geometry by : David Coupier

Download or read book Stochastic Geometry written by David Coupier and published by Springer. This book was released on 2019-04-09 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Analysis for Poisson Point Processes

Stochastic Analysis for Poisson Point Processes

Author: Giovanni Peccati

Publisher: Springer

Published: 2016-07-07

Total Pages: 346

ISBN-13: 3319052330

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Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the mathematical modeling and statistical analysis of telecommunication networks, geostatistics and image analysis. In recent years – due mainly to the impetus of the authors and their collaborators – a powerful connection has been established between stochastic geometry and the Malliavin calculus of variations, which is a collection of probabilistic techniques based on the properties of infinite-dimensional differential operators. This has led in particular to the discovery of a large number of new quantitative limit theorems for high-dimensional geometric objects. This unique book presents an organic collection of authoritative surveys written by the principal actors in this rapidly evolving field, offering a rigorous yet lively presentation of its many facets.


Book Synopsis Stochastic Analysis for Poisson Point Processes by : Giovanni Peccati

Download or read book Stochastic Analysis for Poisson Point Processes written by Giovanni Peccati and published by Springer. This book was released on 2016-07-07 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the mathematical modeling and statistical analysis of telecommunication networks, geostatistics and image analysis. In recent years – due mainly to the impetus of the authors and their collaborators – a powerful connection has been established between stochastic geometry and the Malliavin calculus of variations, which is a collection of probabilistic techniques based on the properties of infinite-dimensional differential operators. This has led in particular to the discovery of a large number of new quantitative limit theorems for high-dimensional geometric objects. This unique book presents an organic collection of authoritative surveys written by the principal actors in this rapidly evolving field, offering a rigorous yet lively presentation of its many facets.

Stochastic Geometry and Its Applications

Stochastic Geometry and Its Applications

Author: Dietrich Stoyan

Publisher: Walter de Gruyter GmbH & Co KG

Published: 1987-12-31

Total Pages: 348

ISBN-13: 3112719174

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No detailed description available for "Stochastic Geometry and Its Applications".


Book Synopsis Stochastic Geometry and Its Applications by : Dietrich Stoyan

Download or read book Stochastic Geometry and Its Applications written by Dietrich Stoyan and published by Walter de Gruyter GmbH & Co KG. This book was released on 1987-12-31 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Stochastic Geometry and Its Applications".

Handbook of Stochastic Analysis and Applications

Handbook of Stochastic Analysis and Applications

Author: D. Kannan

Publisher: CRC Press

Published: 2001-10-23

Total Pages: 800

ISBN-13: 9780824706609

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An introduction to general theories of stochastic processes and modern martingale theory. The volume focuses on consistency, stability and contractivity under geometric invariance in numerical analysis, and discusses problems related to implementation, simulation, variable step size algorithms, and random number generation.


Book Synopsis Handbook of Stochastic Analysis and Applications by : D. Kannan

Download or read book Handbook of Stochastic Analysis and Applications written by D. Kannan and published by CRC Press. This book was released on 2001-10-23 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to general theories of stochastic processes and modern martingale theory. The volume focuses on consistency, stability and contractivity under geometric invariance in numerical analysis, and discusses problems related to implementation, simulation, variable step size algorithms, and random number generation.

Stochastic and Integral Geometry

Stochastic and Integral Geometry

Author: R.V. Ambartzumian

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 135

ISBN-13: 9400939213

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Book Synopsis Stochastic and Integral Geometry by : R.V. Ambartzumian

Download or read book Stochastic and Integral Geometry written by R.V. Ambartzumian and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Stochastic Geometry

Stochastic Geometry

Author: Viktor Benes

Publisher: Springer Science & Business Media

Published: 2007-05-08

Total Pages: 231

ISBN-13: 1402081030

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Stochastic geometry, based on current developments in geometry, probability and measure theory, makes possible modeling of two- and three-dimensional random objects with interactions as they appear in the microstructure of materials, biological tissues, macroscopically in soil, geological sediments etc. In combination with spatial statistics it is used for the solution of practical problems such as the description of spatial arrangements and the estimation of object characteristics. A related field is stereology, which makes possible inference on the structures, based on lower-dimensional observations. Unfolding problems for particle systems and extremes of particle characteristics are studied. The reader can learn about current developments in stochastic geometry with mathematical rigor on one hand and find applications to real microstructure analysis in natural and material sciences on the other hand.


Book Synopsis Stochastic Geometry by : Viktor Benes

Download or read book Stochastic Geometry written by Viktor Benes and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry, based on current developments in geometry, probability and measure theory, makes possible modeling of two- and three-dimensional random objects with interactions as they appear in the microstructure of materials, biological tissues, macroscopically in soil, geological sediments etc. In combination with spatial statistics it is used for the solution of practical problems such as the description of spatial arrangements and the estimation of object characteristics. A related field is stereology, which makes possible inference on the structures, based on lower-dimensional observations. Unfolding problems for particle systems and extremes of particle characteristics are studied. The reader can learn about current developments in stochastic geometry with mathematical rigor on one hand and find applications to real microstructure analysis in natural and material sciences on the other hand.

Stochastic Geometry for Image Analysis

Stochastic Geometry for Image Analysis

Author: Xavier Descombes

Publisher: John Wiley & Sons

Published: 2013-05-06

Total Pages: 215

ISBN-13: 1118601130

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This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.


Book Synopsis Stochastic Geometry for Image Analysis by : Xavier Descombes

Download or read book Stochastic Geometry for Image Analysis written by Xavier Descombes and published by John Wiley & Sons. This book was released on 2013-05-06 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.