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Michel Weber (IRMA, Strasbourg, France )
Dynamical Systems and Processes
ISBN print 978-3-03719-046-3, ISBN online 978-3-03719-546-8DOI 10.4171/046
August 2009, 773 pages, hardcover, 17 x 24 cm.
98.00 Euro
This book presents in a concise and accessible way, as well as in
a common setting, various tools and methods arising from spectral
theory, ergodic theory and stochastic processes theory, which
form the basis of and contribute interactively a great deal to the
current research on almost everywhere convergence problems. The text is divided into four parts.
Part I is devoted to spectral results such as von Neumann’s theorem, spectral regularizations inequalities and
their link with square functions and entropy numbers of ergodic averages.
The representation of a weakly
stationary process as Fourier transform of some random orthogonal measure,
and a study of Gaposhkin’s
spectral criterion conclude this part. Researchers working in dynamical systems and at the crossroads of
spectral theory, ergodic theory and stochastic processes will find the
tools, methods and results presented in this book of great interest.
It is written in a style accessible to graduate students throughout.
Classical results such as mixing in dynamical systems,
Birkhoff's pointwise theorem, dominated ergodic theorems,
oscillations functions of ergodic averages, transference
principle, Wiener–Wintner theorem, Banach principle, continuity principle,
Bourgain's entropy criteria, Burton–Denker’s central limit
theorem are covered in part II.
The metric entropy method and the majorizing measure method, including a
succinct study of Gaussian processes, are treated in part III, with
applications to suprema of random polynomials.
Part IV contains a study of Riemann sums and of the convergence
properties of the system {f(nkx), k ≥ 1}, as well as a probabilistic approach concerning divisors with applications.
Keywords: Dynamical systems, measure-preserving transformation, ergodic theorems, spectral theorems, convergence almost everywhere, central limit theorem, stochastic processes, gaussian processes, metric entropy method, majorizing measure method
Further Information
Review in Zentralblatt MATH 1179.37002
Review in MR 2561719 (2010m:37011)
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