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Author: O. V. Gulinsky
Publisher: Walter de Gruyter GmbH & Co KG
Published: 2019-01-14
Total Pages: 192
ISBN-13: 3110917807
DOWNLOAD EBOOK →No detailed description available for "Large Deviations for Discrete-Time Processes with Averaging".
Author: Yuri Kifer
Publisher: American Mathematical Soc.
Published: 2009-08-07
Total Pages: 144
ISBN-13: 0821844253
DOWNLOAD EBOOK →The work treats dynamical systems given by ordinary differential equations in the form $\frac{dX^\varepsilon(t)}{dt}=\varepsilon B(X^\varepsilon(t),Y^\varepsilon(t))$ where fast motions $Y^\varepsilon$ depend on the slow motion $X^\varepsilon$ (coupled with it) and they are either given by another differential equation $\frac{dY^\varepsilon(t)}{dt}=b(X^\varepsilon(t), Y^\varepsilon(t))$ or perturbations of an appropriate parametric family of Markov processes with freezed slow variables.
Author: Jin Feng
Publisher: American Mathematical Soc.
Published: 2015-02-03
Total Pages: 426
ISBN-13: 1470418703
DOWNLOAD EBOOK →The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.
Author: Keith Burns
Publisher: American Mathematical Soc.
Published: 2008
Total Pages: 358
ISBN-13: 0821842862
DOWNLOAD EBOOK →"This book presents a collection of articles that cover areas of mathematics related to dynamical systems. The authors are well-known experts who use geometric and probabilistic methods to study interesting problems in the theory of dynamical systems and its applications. Some of the articles are surveys while others are original contributions. The topics covered include: Riemannian geometry, models in mathematical physics and mathematical biology, symbolic dynamics, random and stochastic dynamics. This book can be used by graduate students and researchers in dynamical systems and its applications."--BOOK JACKET.
Author: Bronius Grigelionis
Publisher: VSP
Published: 1994-01-01
Total Pages: 756
ISBN-13: 9789067641784
DOWNLOAD EBOOK →This Proceedings volume contains a selection of invited and other papers by international scientists which were presented at the VIth International Vilnius Conference on Probability Theory and Mathematical Statistics, held in Vilnius, Lithuania, 28 June--3 July, 1993. The main topics of the conference were: limit theorems, stochastic analysis and stochastic physics, quantum probability theory, statistics, change detection in random processes, and probabilistic number theory.
Author: Vladimir Panov
Publisher: Springer
Published: 2017-11-21
Total Pages: 511
ISBN-13: 331965313X
DOWNLOAD EBOOK →This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametric methods, acturial science, population dynamics, and many others. The volume is dedicated to Valentin Konakov, head of the International Laboratory of Stochastic Analysis and its Applications on the occasion of his 70th birthday. Contributions were prepared by the participants of the international conference of the international conference “Modern problems of stochastic analysis and statistics”, held at the Higher School of Economics in Moscow from May 29 - June 2, 2016. It offers a valuable reference resource for researchers and graduate students interested in modern stochastics.
Author: Da-Quan Jiang
Publisher: Springer Science & Business Media
Published: 2004
Total Pages: 296
ISBN-13: 9783540206118
DOWNLOAD EBOOK →Author: Mark I. Freidlin
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 442
ISBN-13: 1461206111
DOWNLOAD EBOOK →A treatment of various kinds of limit theorems for stochastic processes defined as a result of random perturbations of dynamical systems. Apart from the long-time behaviour of the perturbed system, exit problems, metastable states, optimal stabilisation, and asymptotics of stationary distributions are considered in detail. The authors'main tools are the large deviation theory, the central limit theorem for stochastic processes, and the averaging principle. The results allow for explicit calculations of the asymptotics of many interesting characteristics of the perturbed system, and most of these results are closely connected with PDEs. This new edition contains expansions on the averaging principle, a new chapter on random perturbations of Hamiltonian systems, along with new results on fast oscillating perturbations of systems with conservation laws. New sections on wave front propagation in semilinear PDEs and on random perturbations of certain infinite-dimensional dynamical systems have been incorporated into the chapter on sharpenings and generalisations.
Author: Ibragimoc
Publisher: CRC Press
Published: 1996-09-01
Total Pages: 336
ISBN-13: 9782919875146
DOWNLOAD EBOOK →First published in 1996. Routledge is an imprint of Taylor & Francis, an informa company.
Author: Thomas J. Sargent
Publisher: Princeton University Press
Published: 2018-06-05
Total Pages: 165
ISBN-13: 0691186685
DOWNLOAD EBOOK →In the past fifteen years, inflation has been conquered by many advanced countries. History reveals, however, that it has been conquered before and returned. In The Conquest of American Inflation, Thomas J. Sargent presents a groundbreaking analysis of the rise and fall of U.S. inflation after 1960. He examines two broad explanations for the behavior of inflation and unemployment in this period: the natural-rate hypothesis joined to the Lucas critique and a more traditional econometric policy evaluation modified to include adaptive expectations and learning. His purpose is not only to determine which is the better account, but also to codify for the benefit of the next generation the economic forces that cause inflation. Sargent begins with an explanation of how American policymakers increased inflation in the early 1960s by following erroneous assumptions about the exploitability of the Phillips curve--the inverse relationship between inflation and unemployment. In subsequent chapters, he connects a sequence of ideas--self-confirming equilibria, least-squares and other adaptive or recursive learning algorithms, convergence of least-squares learners with self-confirming equilibria, and recurrent dynamics along escape routes from self-confirming equilibria. Sargent synthesizes results from macroeconomics, game theory, control theory, and other fields to extend both adaptive expectations and rational expectations theory, and he compellingly describes postwar inflation in terms of drifting coefficients. He interprets his results in favor of adaptive expectations as the relevant mechanism affecting inflation policy. Providing an original methodological link between theoretical and policy economics, this book will engender much debate and become an indispensable text for academics, graduate students, and professional economists.
