TY  - BOOK
AU  - Klyatskin,Valery I.
TI  - Dynamics of Stochastic Systems
SN  - 9780080504858
U1  - 519.23 22
PY  - 2005///
CY  - Burlington
PB  - Elsevier
KW  - Statistical physics
KW  - Stochastic processes
KW  - Stochastic analysis
N1  - Front Cover; DYNAMICS OF STOCHASTIC SYSTEMS; Copyright Page; Preface; Contents; Introduction; Part I: Dynamical description of stochastic systems; Chapter 1. Examples, basic problems, peculiar features of solutions; Chapter 2. Solution dependence on problem type, medium parameters, and initial data; Chapter 3. Indicator function and Liouville equation; Part II: Statistical description of stochastic systems; Chapter 4. Random quantities, processes and fields; Chapter 5. Correlation splitting; Chapter 6. General approaches to analyzing stochastic dynamic systems; Chapter 7. Stochastic equations with the Markovian fluctuations of parametersChapter 8. Gaussian delta-correlated random field (ordinary differential equations); Chapter 9. Methods for solving and analyzing the Fokker-Planck equation; Chapter 10. Gaussian delta-correlated random field (causal integral equations); Part III: Examples of coherent phenomena in stochastic dynamic systems; Chapter 11. Passive tracer clustering and diffusion in random
N2  - 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 scatteri
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