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Dynamics of stochastic systems /

Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kli͡at͡skin, V. I. (Valeriĭ Isaakovich)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, 2005.
Edición:1st ed.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Kli͡at͡skin, V. I.  |q (Valeriĭ Isaakovich) 
245 1 0 |a Dynamics of stochastic systems /  |c V.I. Klyatskin. 
250 |a 1st ed. 
260 |a Amsterdam :  |b Elsevier,  |c 2005. 
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520 |a Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''oil slicks''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere. Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields. The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data. This raises a host of challenging mathematical issues. One could rarely solve such systems exactly (or approximately) in a closed analytic form, and their solutions depend in a complicated implicit manner on the initial-boundary data, forcing and system's (media) parameters . In mathematical terms such solution becomes a complicated "nonlinear functional" of random fields and processes. Part I gives mathematical formulation for the basic physical models of transport, diffusion, propagation and develops some analytic tools. Part II sets up and applies the techniques of variational calculus and stochastic analysis, like Fokker-Plank equation to those models, to produce exact or approximate solutions, or in worst case numeric procedures. The exposition is motivated and demonstrated with numerous examples. Part III takes up issues for the coherent phenomena in stochastic dynamical systems, described by ordinary and partial differential equations, like wave propagation in randomly layered media (localization), turbulent advection of passive tracers (clustering). Each chapter is appended with problems the reader to solve by himself (herself), which will be a good training for independent investigations. This book is translation from Russian and is completed with new principal results of recent research. The book develops mathematical tools of stochastic analysis, and applies them to a wide range of physical models of particles, fluids, and waves. Accessible to a broad audience with general background in mathematical physics, but no special expertise in stochastic analysis, wave propagation or turbulence 
505 0 |a Contents -- Preface -- Introduction -- I Dynamical description of stochastic systems -- 1 Examples, basic problems, peculiar features of solutions -- 2 Indicator function and Liouville equation -- 3 Random quantities, processes and fields -- 4 Correlation splitting -- 5 General approaches to analyzing stochastic dynamic systems -- 6 Stochastic equations with the Markovian fluctuations of parameters -- 7 Gaussian random field delta-correlated in time (ordinary differential equations) -- 8 Methods for solving and analyzing the Fokker-Planck equation -- 9 Gaussian delta-correlated random field (causal integral equations) -- 10 Diffusion approximation -- 11 Passive tracer clustering and diffusion in random hydrodynamic flows -- 12 Wave localization in randomly layered media -- 13 Wave propagation in random inhomogeneous medium -- 14 Some problems of statistical hydrodynamics -- V Appendix -- A Variation (functional) derivatives -- B Fundamental solutions of wave problems in empty and layered media -- C Imbedding method in boundary-value wave problems 380 -- Bibliography -- Index. 
504 |a Includes bibliographical references (pages 200-203) and index. 
588 0 |a Print version record. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Stochastic analysis. 
650 0 |a Statistical physics. 
650 0 |a Stochastic processes. 
650 6 |a Analyse stochastique. 
650 6 |a Physique statistique. 
650 6 |a Processus stochastiques. 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a Statistical physics  |2 fast 
650 7 |a Stochastic analysis  |2 fast 
650 7 |a Stochastic processes  |2 fast 
776 0 8 |i Print version:  |a Kli͡at͡skin, Valeriĭ Isaakovich.  |t Dynamics of stochastic systems.  |b 1st ed.  |d Amsterdam : Elsevier, 2005  |z 0444517960  |z 9780444517968  |w (OCoLC)60520318 
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