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Probabilistic Models For Nonlinear Partial Differential Equations
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Book Synopsis Probabilistic Models for Nonlinear Partial Differential Equations by : Denis Talay
Download or read book Probabilistic Models for Nonlinear Partial Differential Equations written by Denis Talay and published by Springer. This book was released on 2006-11-13 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The lecture courses of the CIME Summer School on Probabilistic Models for Nonlinear PDE's and their Numerical Applications (April 1995) had a three-fold emphasis: first, on the weak convergence of stochastic integrals; second, on the probabilistic interpretation and the particle approximation of equations coming from Physics (conservation laws, Boltzmann-like and Navier-Stokes equations); third, on the modelling of networks by interacting particle systems. This book, collecting the notes of these courses, will be useful to probabilists working on stochastic particle methods and on the approximation of SPDEs, in particular, to PhD students and young researchers.
Book Synopsis Probabilistic Models for Nonlinear Partial Differential Equations by :
Download or read book Probabilistic Models for Nonlinear Partial Differential Equations written by and published by . This book was released on 1996 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probability and Partial Differential Equations in Modern Applied Mathematics by : Edward C. Waymire
Download or read book Probability and Partial Differential Equations in Modern Applied Mathematics written by Edward C. Waymire and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Probability and Partial Differential Equations in Modern Applied Mathematics" is devoted to the role of probabilistic methods in modern applied mathematics from the perspectives of both a tool for analysis and as a tool in modeling. There is a recognition in the applied mathematics research community that stochastic methods are playing an increasingly prominent role in the formulation and analysis of diverse problems of contemporary interest in the sciences and engineering. A probabilistic representation of solutions to partial differential equations that arise as deterministic models allows one to exploit the power of stochastic calculus and probabilistic limit theory in the analysis of deterministic problems, as well as to offer new perspectives on the phenomena for modeling purposes. There is also a growing appreciation of the role for the inclusion of stochastic effects in the modeling of complex systems. This has led to interesting new mathematical problems at the interface of probability, dynamical systems, numerical analysis, and partial differential equations. This volume will be useful to researchers and graduate students interested in probabilistic methods, dynamical systems approaches and numerical analysis for mathematical modeling in the sciences and engineering.
Book Synopsis Superdiffusions and Positive Solutions of Nonlinear Partial Differential Equations by : Evgeniĭ Borisovich Dynkin
Download or read book Superdiffusions and Positive Solutions of Nonlinear Partial Differential Equations written by Evgeniĭ Borisovich Dynkin and published by American Mathematical Soc.. This book was released on 2004 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the applications of probability theory to the theory of nonlinear partial differential equations. More precisely, it is shown that all positive solutions for a class of nonlinear elliptic equations in a domain are described in terms of their traces on the boundary of the domain. The main probabilistic tool is the theory of superdiffusions, which describes a random evolution of a cloud of particles. A substantial enhancement of this theory is presented that will be of interest to anyone who works on applications of probabilistic methods to mathematical analysis. The book is suitable for graduate students and research mathematicians interested in probability theory and its applications to differential equations. Also of interest by this author is Diffusions, Superdiffusions and Partial Differential Equations in the AMS series, Colloquium Publications.
Book Synopsis Probabilistic Methods in Partial Differential Equations by : Steven Orey
Download or read book Probabilistic Methods in Partial Differential Equations written by Steven Orey and published by . This book was released on 1980* with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamical Systems and Probabilistic Methods in Partial Differential Equations by : Percy Deift
Download or read book Dynamical Systems and Probabilistic Methods in Partial Differential Equations written by Percy Deift and published by American Mathematical Soc.. This book was released on 1996 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains some of the lectures presented in June 1994 during the AMS-SIAM Summer Seminar at the Mathematical Sciences Research Institute in Berkeley. The goal of the seminar was to introduce participants to as many interesting and active applications of dynamical systems and probabilistic methods to problems in applied mathematics as possible. As a result, this book covers a great deal of ground. Nevertheless, the pedagogical orientation of the lectures has been retained, and therefore the book will serve as an ideal introduction to these varied and interesting topics.
Book Synopsis Nonlinear Differential Equation Models by : Ansgar Jüngel
Download or read book Nonlinear Differential Equation Models written by Ansgar Jüngel and published by Springer Science & Business Media. This book was released on 2004-06-14 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this book originate from lectures which were held at the "Vienna Workshop on Nonlinear Models and Analysis" – May 20–24, 2002. They represent a cross-section of the research field Applied Nonlinear Analysis with emphasis on free boundaries, fully nonlinear partial differential equations, variational methods, quasilinear partial differential equations and nonlinear kinetic models.
Book Synopsis Stochastic Differential Equations, Backward SDEs, Partial Differential Equations by : Etienne Pardoux
Download or read book Stochastic Differential Equations, Backward SDEs, Partial Differential Equations written by Etienne Pardoux and published by Springer. This book was released on 2014-06-24 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph presents results to researchers in stochastic calculus, forward and backward stochastic differential equations, connections between diffusion processes and second order partial differential equations (PDEs), and financial mathematics. It pays special attention to the relations between SDEs/BSDEs and second order PDEs under minimal regularity assumptions, and also extends those results to equations with multivalued coefficients. The authors present in particular the theory of reflected SDEs in the above mentioned framework and include exercises at the end of each chapter. Stochastic calculus and stochastic differential equations (SDEs) were first introduced by K. Itô in the 1940s, in order to construct the path of diffusion processes (which are continuous time Markov processes with continuous trajectories taking their values in a finite dimensional vector space or manifold), which had been studied from a more analytic point of view by Kolmogorov in the 1930s. Since then, this topic has become an important subject of Mathematics and Applied Mathematics, because of its mathematical richness and its importance for applications in many areas of Physics, Biology, Economics and Finance, where random processes play an increasingly important role. One important aspect is the connection between diffusion processes and linear partial differential equations of second order, which is in particular the basis for Monte Carlo numerical methods for linear PDEs. Since the pioneering work of Peng and Pardoux in the early 1990s, a new type of SDEs called backward stochastic differential equations (BSDEs) has emerged. The two main reasons why this new class of equations is important are the connection between BSDEs and semilinear PDEs, and the fact that BSDEs constitute a natural generalization of the famous Black and Scholes model from Mathematical Finance, and thus offer a natural mathematical framework for the formulation of many new models in Finance.
Book Synopsis Stochastic Simulation and Monte Carlo Methods by : Carl Graham
Download or read book Stochastic Simulation and Monte Carlo Methods written by Carl Graham and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.
Book Synopsis Analytical Properties of Nonlinear Partial Differential Equations by : Alexei Cheviakov
Download or read book Analytical Properties of Nonlinear Partial Differential Equations written by Alexei Cheviakov and published by Springer Nature. This book was released on with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Superdiffusions and Positive Solutions of Nonlinear Partial Differential Equations by : Evgeniĭ Borisovich Dynkin
Download or read book Superdiffusions and Positive Solutions of Nonlinear Partial Differential Equations written by Evgeniĭ Borisovich Dynkin and published by American Mathematical Soc.. This book was released on 2004 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the applications of probability theory to the theory of nonlinear partial differential equations. More precisely, it is shown that all positive solutions for a class of nonlinear elliptic equations in a domain are described in terms of their traces on the boundary of the domain. The main probabilistic tool is the theory of superdiffusions, which describes a random evolution of a cloud of particles. A substantial enhancement of this theory is presented that will be of interest to anyone who works on applications of probabilistic methods to mathematical analysis. The book is suitable for graduate students and research mathematicians interested in probability theory and its applications to differential equations. Also of interest by this author is ""Diffusions, Superdiffusions and Partial Differential Equations"" in the ""AMS"" series, Colloquium Publications.
Book Synopsis Surveys in Applied Mathematics by : Mark I. Freidlin
Download or read book Surveys in Applied Mathematics written by Mark I. Freidlin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 2 offers three in-depth articles covering significant areas in applied mathematics research. Chapters feature numerous illustrations, extensive background material and technical details, and abundant examples. The authors analyze nonlinear front propagation for a large class of semilinear partial differential equations using probabilistic methods; examine wave localization phenomena in one-dimensional random media; and offer an extensive introduction to certain model equations for nonlinear wave phenomena.
Book Synopsis Partial Differential Equations in Action by : Sandro Salsa
Download or read book Partial Differential Equations in Action written by Sandro Salsa and published by Springer. This book was released on 2015-04-24 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is intended as an advanced undergraduate or first-year graduate course for students from various disciplines, including applied mathematics, physics and engineering. It has evolved from courses offered on partial differential equations (PDEs) over the last several years at the Politecnico di Milano. These courses had a twofold purpose: on the one hand, to teach students to appreciate the interplay between theory and modeling in problems arising in the applied sciences, and on the other to provide them with a solid theoretical background in numerical methods, such as finite elements. Accordingly, this textbook is divided into two parts. The first part, chapters 2 to 5, is more elementary in nature and focuses on developing and studying basic problems from the macro-areas of diffusion, propagation and transport, waves and vibrations. In turn the second part, chapters 6 to 11, concentrates on the development of Hilbert spaces methods for the variational formulation and the analysis of (mainly) linear boundary and initial-boundary value problems.
Book Synopsis Stochastic Ordinary and Stochastic Partial Differential Equations by : Peter Kotelenez
Download or read book Stochastic Ordinary and Stochastic Partial Differential Equations written by Peter Kotelenez and published by Springer Science & Business Media. This book was released on 2007-12-05 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Partial Differential Equations analyzes mathematical models of time-dependent physical phenomena on microscopic, macroscopic and mesoscopic levels. It provides a rigorous derivation of each level from the preceding one and examines the resulting mesoscopic equations in detail. Coverage first describes the transition from the microscopic equations to the mesoscopic equations. It then covers a general system for the positions of the large particles.
Download or read book Nonlinear PDEs written by Marius Ghergu and published by Springer. This book was released on 2011-10-29 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emphasis throughout the present volume is on the practical application of theoretical mathematical models helping to unravel the underlying mechanisms involved in processes from mathematical physics and biosciences. It has been conceived as a unique collection of abstract methods dealing especially with nonlinear partial differential equations (either stationary or evolutionary) that are applied to understand concrete processes involving some important applications related to phenomena such as: boundary layer phenomena for viscous fluids, population dynamics,, dead core phenomena, etc. It addresses researchers and post-graduate students working at the interplay between mathematics and other fields of science and technology and is a comprehensive introduction to the theory of nonlinear partial differential equations and its main principles also presents their real-life applications in various contexts: mathematical physics, chemistry, mathematical biology, and population genetics. Based on the authors' original work, this volume provides an overview of the field, with examples suitable for researchers but also for graduate students entering research. The method of presentation appeals to readers with diverse backgrounds in partial differential equations and functional analysis. Each chapter includes detailed heuristic arguments, providing thorough motivation for the material developed later in the text. The content demonstrates in a firm way that partial differential equations can be used to address a large variety of phenomena occurring in and influencing our daily lives. The extensive reference list and index make this book a valuable resource for researchers working in a variety of fields and who are interested in phenomena modeled by nonlinear partial differential equations.
Book Synopsis Stochastic Ordinary and Stochastic Partial Differential Equations by : Peter Kotelenez
Download or read book Stochastic Ordinary and Stochastic Partial Differential Equations written by Peter Kotelenez and published by Springer. This book was released on 2014-09-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Partial Differential Equations analyzes mathematical models of time-dependent physical phenomena on microscopic, macroscopic and mesoscopic levels. It provides a rigorous derivation of each level from the preceding one and examines the resulting mesoscopic equations in detail. Coverage first describes the transition from the microscopic equations to the mesoscopic equations. It then covers a general system for the positions of the large particles.
Book Synopsis Reduced Basis Methods for Partial Differential Equations by : Alfio Quarteroni
Download or read book Reduced Basis Methods for Partial Differential Equations written by Alfio Quarteroni and published by Springer. This book was released on 2015-08-19 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a basic introduction to reduced basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs) arising from engineering and applied sciences, such as PDEs depending on several parameters and PDE-constrained optimization. The book presents a general mathematical formulation of RB methods, analyzes their fundamental theoretical properties, discusses the related algorithmic and implementation aspects, and highlights their built-in algebraic and geometric structures. More specifically, the authors discuss alternative strategies for constructing accurate RB spaces using greedy algorithms and proper orthogonal decomposition techniques, investigate their approximation properties and analyze offline-online decomposition strategies aimed at the reduction of computational complexity. Furthermore, they carry out both a priori and a posteriori error analysis. The whole mathematical presentation is made more stimulating by the use of representative examples of applicative interest in the context of both linear and nonlinear PDEs. Moreover, the inclusion of many pseudocodes allows the reader to easily implement the algorithms illustrated throughout the text. The book will be ideal for upper undergraduate students and, more generally, people interested in scientific computing. All these pseudocodes are in fact implemented in a MATLAB package that is freely available at https://github.com/redbkit
