The Dirichlet Space and Related Function Spaces, Nicola Arcozzi, Richard Rochberg, Eric T. Sawyer, Brett D. Wick
Автор: El-Fallah Название: A Primer on the Dirichlet Space ISBN: 1107047528 ISBN-13(EAN): 9781107047525 Издательство: Cambridge Academ Рейтинг: Цена: 70750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This systematic account of the Dirichlet space provides an introduction that will be valuable to researchers in function theory, assembling results previously only found in scattered research articles. Containing more than 100 exercises, the book is also suitable for self-study by graduate students in mathematics.
Автор: Andreas Defant, Domingo Garcia, Manuel Maestre, Pablo Sevilla-Peris Название: Dirichlet Series and Holomorphic Functions in High Dimensions ISBN: 1108476716 ISBN-13(EAN): 9781108476713 Издательство: Cambridge Academ Рейтинг: Цена: 185850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Over 100 years ago Harald Bohr identified a deep problem about the convergence of Dirichlet series. In recent years there has been a substantial revival of interest in this topic, and the goal of this book is to describe in detail some of its key elements to a wide audience.
Автор: Yoichi Oshima Название: Semi-Dirichlet Forms and Markov Processes ISBN: 3110302004 ISBN-13(EAN): 9783110302004 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Thisbook deals with analytic treatments of Markov processes. Symmetric Dirichlet forms andtheir associated Markov processes are important and powerful toolsin the theory of Markovprocesses and their applications. The theoryis well studied and used in various fields. In this monograph, we intend togeneralize the theory to non-symmetric and time dependent semi-Dirichlet forms. By this generalization, we can cover the wide class of Markov processes and analytic theory which do not possess the dualMarkov processes. In particular, under the semi-Dirichlet form setting, the stochastic calculus is not well established yet.In this monograph, we intend to give an introduction to such calculus. Furthermore, basic examples different from the symmetric cases are given.Thetext is writtenfor graduate students, but alsoresearchers.
Domain decomposition (DD) methods provide powerful tools for constructing parallel numerical solution algorithms for large scale systems of algebraic equations arising from the discretization of partial differential equations. These methods are well-established and belong to a fast developing area. In this volume, the reader will find a brief historical overview, the basic results of the general theory of domain and space decomposition methods as well as the description and analysis of practical DD algorithms for parallel computing. It is typical to find in this volume that most of the presented DD solvers belong to the family of fast algorithms, where each component is efficient with respect to the arithmetical work. Readers will discover new analysis results for both the well-known basic DD solvers and some DD methods recently devised by the authors, e.g., for elliptic problems with varying chaotically piecewise constant orthotropism without restrictions on the finite aspect ratios.
The hp finite element discretizations, in particular, by spectral elements of elliptic equations are given significant attention in current research and applications. This volume is the first to feature all components of Dirichlet-Dirichlet-type DD solvers for hp discretizations devised as numerical procedures which result in DD solvers that are almost optimal with respect to the computational work. The most important DD solvers are presented in the matrix/vector form algorithms that are convenient for practical use.
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