Functional Analytic Techniques for Diffusion Processes

Functional Analytic Techniques for Diffusion Processes

Author: Kazuaki Taira

Publisher: Springer Nature

Published: 2022-05-28

Total Pages: 792

ISBN-13: 9811910995

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This book is an easy-to-read reference providing a link between functional analysis and diffusion processes. More precisely, the book takes readers to a mathematical crossroads of functional analysis (macroscopic approach), partial differential equations (mesoscopic approach), and probability (microscopic approach) via the mathematics needed for the hard parts of diffusion processes. This work brings these three fields of analysis together and provides a profound stochastic insight (microscopic approach) into the study of elliptic boundary value problems. The author does a massive study of diffusion processes from a broad perspective and explains mathematical matters in a more easily readable way than one usually would find. The book is amply illustrated; 14 tables and 141 figures are provided with appropriate captions in such a fashion that readers can easily understand powerful techniques of functional analysis for the study of diffusion processes in probability. The scope of the author’s work has been and continues to be powerful methods of functional analysis for future research of elliptic boundary value problems and Markov processes via semigroups. A broad spectrum of readers can appreciate easily and effectively the stochastic intuition that this book conveys. Furthermore, the book will serve as a sound basis both for researchers and for graduate students in pure and applied mathematics who are interested in a modern version of the classical potential theory and Markov processes. For advanced undergraduates working in functional analysis, partial differential equations, and probability, it provides an effective opening to these three interrelated fields of analysis. Beginning graduate students and mathematicians in the field looking for a coherent overview will find the book to be a helpful beginning. This work will be a major influence in a very broad field of study for a long time.


Diffusion Processes and Partial Differential Equations

Diffusion Processes and Partial Differential Equations

Author: Kazuaki Taira

Publisher:

Published: 1988

Total Pages: 480

ISBN-13:

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This book provides a careful and accessible exposition of functional analytic methods in stochastic analysis. It focuses on the relationship between Markov processes and elliptic boundary value problems and explores several recent developments in the theory of partial differential equations which have made further progress in the study of Markov processes possible. This book will have great appeal to both advanced students and researchers as an introduction to three interrelated subjects in analysis (Markov processes, semigroups, and elliptic boundary value problems), providing powerful methods for future research.


Diffusion Processes and Partial Differential Equations

Diffusion Processes and Partial Differential Equations

Author: Kazuaki Taira

Publisher:

Published: 1988

Total Pages: 480

ISBN-13:

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This book provides a careful and accessible exposition of functional analytic methods in stochastic analysis. It focuses on the relationship between Markov processes and elliptic boundary value problems and explores several recent developments in the theory of partial differential equations which have made further progress in the study of Markov processes possible. This book will have great appeal to both advanced students and researchers as an introduction to three interrelated subjects in analysis (Markov processes, semigroups, and elliptic boundary value problems), providing powerful methods for future research.


Stochastic Processes and Applications

Stochastic Processes and Applications

Author: Grigorios A. Pavliotis

Publisher: Springer

Published: 2014-11-19

Total Pages: 345

ISBN-13: 1493913239

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This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.


Analysis For Diffusion Processes On Riemannian Manifolds

Analysis For Diffusion Processes On Riemannian Manifolds

Author: Feng-yu Wang

Publisher: World Scientific

Published: 2013-09-23

Total Pages: 392

ISBN-13: 9814452661

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Stochastic analysis on Riemannian manifolds without boundary has been well established. However, the analysis for reflecting diffusion processes and sub-elliptic diffusion processes is far from complete. This book contains recent advances in this direction along with new ideas and efficient arguments, which are crucial for further developments. Many results contained here (for example, the formula of the curvature using derivatives of the semigroup) are new among existing monographs even in the case without boundary.


Inference for Diffusion Processes

Inference for Diffusion Processes

Author: Christiane Fuchs

Publisher: Springer Science & Business Media

Published: 2013-01-18

Total Pages: 439

ISBN-13: 3642259693

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Diffusion processes are a promising instrument for realistically modelling the time-continuous evolution of phenomena not only in the natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often carried out incorrectly, and the according statistical inference is considered almost exclusively by theoreticians. This book explains both topics in an illustrative way which also addresses practitioners. It provides a complete overview of the current state of research and presents important, novel insights. The theory is demonstrated using real data applications.


Multidimensional Diffusion Processes

Multidimensional Diffusion Processes

Author: Daniel W. Stroock

Publisher: Springer

Published: 2007-02-03

Total Pages: 338

ISBN-13: 3540289992

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From the reviews: "This book is an excellent presentation of the application of martingale theory to the theory of Markov processes, especially multidimensional diffusions. [...] This monograph can be recommended to graduate students and research workers but also to all interested in Markov processes from a more theoretical point of view." Mathematische Operationsforschung und Statistik


Topics in Functional Analysis and Applications

Topics in Functional Analysis and Applications

Author: S. Kesavan

Publisher: John Wiley & Sons

Published: 1989

Total Pages: 267

ISBN-13: 9780470210505

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Present day research in partial differential equations uses a lot of functional analytic techniques. This book treats these methods concisely, in one volume, at the graduate level. It introduces distribution theory (which is fundamental to the study of partial differential equations) and Sobolev spaces (the natural setting in which to find generalized solutions of PDE). Examples, counter-examples, and exercises are included.