Handbook of Dynamics and Probability - Müller, Peter
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Présentation Handbook Of Dynamics And Probability Format Relié
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Résumé : Introduction.- I Dynamics.- Deterministic dynamical systems.- Linear and integrable systems.- Stability and long-time behavior.- Ergodic theory.- Numerical Algorithms.- II Probability.- Probability Theory.- Discrete-time stochastic processes.- Continuous-time stochastic processes.- Information entropy.- III Probability in dynamical evolution .- Time evolution of broadened initial states.- Stochastic processes generated by observables.- Stochastic dynamical systems.- IV Probability in scientific reasoning.- Interpretations of probability.- Parameter estimation and hypothesis testing.- Bayesian inferences.- V Probability in physics.- Equilibrium statistical mechanics.- Non-equilibrium statistical mechanics.- Foundational issues of statistical mechanics.- Quantum Mechanics.- A Classical Mechanics.- B Thermostatics.- C Fluid dynamics.- D Some proofs and explicit computations.- E Mathematical tools, conventions and notation.- References.- Index.
Biographie:
Peter M?ller studied physics and mathematics at the University of Hamburg. He received his Diplom degree (Physics) in 1970 , his Ph.D. (Geophysics) in 1974, and his habilitation (Geophysics) in 1981. He worked at Harvard University as a research associate before moving to the University of Hawaii in 1982, where he was a professor of Oceanography in the School of Ocean and Earth Science and Technology until his retirement in 2013. He is now a professor emeritus. His research interests cover a broad range of topics in oceanography and climate research, especially wave dynamics, stochastic (climate) models, and foundations of complex system theories. He has published two books and numerous articles. Peter M?ller was the organizer of the 'Aha Huliko'a Hawaiian Winter Workshop series and for ten years the chief editor of the Journal of Physical Oceanography..
Sommaire: Introduction I Dynamics Deterministic dynamical systems Linear and integrable systems Stability and long-time behavior Ergodic theory Numerical Algorithms II Probability Probability Theory Discrete-time stochastic processes Continuous-time stochastic processes Information entropy III Probability in dynamical evolution Time evolution of broadened initial states Stochastic processes generated by observables Stochastic dynamical systems IV Probability in scientific reasoning Interpretations of probability Parameter estimation and hypothesis testing Bayesian inferences V Probability in physics Equilibrium statistical mechanics Non-equilibrium statistical mechanics Foundational issues of statistical mechanics Quantum Mechanics A Classical Mechanics B Thermostatics D Some proofs and explicit computations E Mathematical tools, conventions and notation References Index
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