<p>Asymptotical problems have always played an important role in probability theory. In classical probability theory dealing mainly with sequences of independent variables, theorems of the type of laws of large numbers, theorems of the type of the central limit theorem, and theorems on large deviati
Random Perturbations of Dynamical Systems
β Scribed by Mark I. Freidlin, Alexander D. Wentzell (auth.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2012
- Tongue
- English
- Leaves
- 482
- Series
- Grundlehren der mathematischen Wissenschaften 260
- Edition
- 3
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Many notions and results presented in the previous editions of this volume have since become quite popular in applications, and many of them have been βrediscoveredβ in applied papers.
In the present 3rd edition small changes were made to the chapters in which long-time behavior of the perturbed system is determined by large deviations. Most of these changes concern terminology. In particular, it is explained that the notion of sub-limiting distribution for a given initial point and a time scale is identical to the idea of metastability, that the stochastic resonance is a manifestation of metastability, and that the theory of this effect is a part of the large deviation theory. The reader will also find new comments on the notion of quasi-potential that the authors introduced more than forty years ago, and new references to recent papers in which the proofs of some conjectures included in previous editions have been obtained.
Apart from the above mentioned changes the main innovations in the 3rd edition concern the averaging principle. A new Section on deterministic perturbations of one-degree-of-freedom systems was added in Chapter 8. It is shown there that pure deterministic perturbations of an oscillator may lead to a stochastic, in a certain sense, long-time behavior of the system, if the corresponding Hamiltonian has saddle points. The usefulness of a joint consideration of classical theory of deterministic perturbations together with stochastic perturbations is illustrated in this section. Also a new Chapter 9 has been inserted in which deterministic and stochastic perturbations of systems with many degrees of freedom are considered. Because of the resonances, stochastic regularization in this case is even more important.
β¦ Table of Contents
Front Matter....Pages I-XXVIII
Random Perturbations....Pages 1-28
Small Random Perturbations on a Finite Time Interval....Pages 29-53
Action Functional....Pages 54-84
Gaussian Perturbations of Dynamical Systems. Neighborhood of an Equilibrium Point....Pages 85-116
Perturbations Leading to Markov Processes....Pages 117-141
Markov Perturbations on Large Time Intervals....Pages 142-191
The Averaging Principle. Fluctuations in Dynamical Systems with Averaging....Pages 192-257
Random Perturbations of Hamiltonian Systems....Pages 258-354
The Multidimensional Case....Pages 355-389
Stability Under Random Perturbations....Pages 390-404
Sharpenings and Generalizations....Pages 405-440
Back Matter....Pages 441-458
β¦ Subjects
Probability Theory and Stochastic Processes
π SIMILAR VOLUMES
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 a
<p><p>Many notions and results presented in the previous editions of this volume have since become quite popular in applications, and many of them have been βrediscoveredβ in applied papers. <br><br>In the present 3rd edition small changes were made to the chapters in which long-time behavior of the
<p>Mathematicians often face the question to which extent mathematical models describe processes of the real world. These models are derived from experimental data, hence they describe real phenomena only approximately. Thus a mathematical approach must begin with choosing properties which are not v
<p>Asymptotical problems have always played an important role in probability theory. In classical probability theory dealing mainly with sequences of independent variables, theorems of the type of laws of large numbers, theorems of the type of the central limit theorem, and theorems on large deviati