Functional Analytic Techniques for Diffusion Processes

Functional Analytic Techniques for Diffusion Processes
Author: Kazuaki Taira
Publisher: Springer Nature
Total Pages: 792
Release: 2022-05-28
Genre: Mathematics
ISBN: 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:
Total Pages: 480
Release: 1988
Genre: Mathematics
ISBN:

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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:
Total Pages: 480
Release: 1988
Genre: Mathematics
ISBN:

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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
Total Pages: 345
Release: 2014-11-19
Genre: Mathematics
ISBN: 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.

Multidimensional Diffusion Processes

Multidimensional Diffusion Processes
Author: Daniel W. Stroock
Publisher: Springer
Total Pages: 338
Release: 2007-02-03
Genre: Mathematics
ISBN: 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

Statistical Inference for Ergodic Diffusion Processes

Statistical Inference for Ergodic Diffusion Processes
Author: Yury A. Kutoyants
Publisher: Springer Science & Business Media
Total Pages: 493
Release: 2013-03-09
Genre: Mathematics
ISBN: 144713866X

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The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.

Diffusion Processes and Related Problems in Analysis, Volume I

Diffusion Processes and Related Problems in Analysis, Volume I
Author: Mark A. Pinsky
Publisher: Birkhäuser
Total Pages: 544
Release: 1990
Genre: Mathematics
ISBN:

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During the week of October 23-27,1989, Northwestern University hosted an international conference on the theme "Diffusion Processes and Related Problems in Analysis." This was attended by 105 partici pants representing 14 different countries. The conference, which is part of the "Emphasis Year" program traditionally supported by the Mathematics Department, was additionally supported by grants from the National Science Foundation, the National Security Agency, the Institute for Mathematics and Applications, as well as by supplemen tary sources from Northwestern University. The purpose of this meeting was to bring together workers in vari ous parts of probability theory, mathematical physics, and partial dif ferential equations. Previous efforts in this direction were represented by the 1987 AMS Summer Research Conference "Geometry of Random Motion" co-sponsored with Rick Durrett, the proceedings of which ap peared as volume 73 in the AMS series "Contemporary Mathematics." The present effort is intended to extend beyond the strictly geometric theme and to include problems of large deviations, stochastic flows, and other areas of stochastic analysis in which diffusion processes play a leading role.

Topics in Functional Analysis and Applications

Topics in Functional Analysis and Applications
Author: S. Kesavan
Publisher: John Wiley & Sons
Total Pages: 267
Release: 1989
Genre: Analyse fonctionnelle
ISBN: 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.