Upper and Lower Bounds for Stochastic Processes, Michel Talagrand
Автор: Gallager Название: Stochastic Processes ISBN: 1107039754 ISBN-13(EAN): 9781107039759 Издательство: Cambridge Academ Рейтинг: Цена: 11246.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.
Автор: Doob J.l. Название: Stochastic processes ISBN: 0471523690 ISBN-13(EAN): 9780471523697 Издательство: Wiley Рейтинг: Цена: 19398.00 р. 27712.00-30% Наличие на складе: Есть (1 шт.) Описание: A systematic account of the development of stochastic processes over the last 20 years. A supplement contained within the text includes a treatment of the various aspects of measure theory. There is also a chapter on the specialized problem of prediction theory.
Автор: N.G. Van Kampen Название: Stochastic Processes in Physics and Chemistry, ISBN: 0444529659 ISBN-13(EAN): 9780444529657 Издательство: Elsevier Science Рейтинг: Цена: 15157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Replaces the contrived application of the quantum master equation with a satisfactory treatment of quantum fluctuations. This work covers the fluctuations and stochastic methods for describing them. It is of interest to students and researchers in applied mathematics, physics and physical chemistry.
Автор: Kozachenko, Yuriy V. Название: Simulation of Stochastic Processes with Given Accuracy and Reliab ISBN: 1785482173 ISBN-13(EAN): 9781785482175 Издательство: Elsevier Science Рейтинг: Цена: 29139.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Simulation has now become an integral part of research and development across many fields of study. Despite the large amounts of literature in the field of simulation and modeling, one recurring problem is the issue of accuracy and confidence level of constructed models. By outlining the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and reliability in functional spaces. The authors explore analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processes and Cox processes. Methods of simulation of stochastic processes and fields with given accuracy and reliability in some Banach spaces are also considered.
Provides an analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processes
Contains information on the study of the issue of accuracy and confidence level of constructed models not found in other books on the topic
Provides methods and tools in measuring accuracy and reliability in functional spaces
Автор: Ibe Oliver Название: Markov Processes for Stochastic Modeling (Revised) ISBN: 0323282954 ISBN-13(EAN): 9780323282956 Издательство: Elsevier Science Рейтинг: Цена: 11789.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. . Covering a wide range ofareas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory toprovide a solid groundin the subject forthe reader.
Описание: The book introduces new ways of using analytic number theory in cryptography and related areas, such as complexity theory and pseudorandom number generation.Cryptographers and number theorists will find this book useful. The former can learn about new number theoretic techniques which have proved to be invaluable cryptographic tools, the latter about new challenging areas of applications of their skills.
Автор: Jacod Jean, Shiryaev Albert N. Название: Limit Theorems for Stochastic Processes ISBN: 3540439323 ISBN-13(EAN): 9783540439325 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Initially the theory of convergence in law of stochastic processes was developed quite independently from the theory of martingales, semimartingales and stochastic integrals. Apart from a few exceptions essentially concerning diffusion processes, it is only recently that the relation between the two theories has been thoroughly studied. The authors of this Grundlehren volume, two of the international leaders in the field, propose a systematic exposition of convergence in law for stochastic processes, from the point of view of semimartingale theory, with emphasis on results that are useful for mathematical theory and mathematical statistics. This leads them to develop in detail some particularly useful parts of the general theory of stochastic processes, such as martingale problems, and absolute continuity or contiguity results. The book contains an introduction to the theory of martingales and semimartingales, random measures stochastic integrales, Skorokhod topology, etc., as well as a large number of results which have never appeared in book form, and some entirely new results. The second edition contains some additions to the text and references. Some parts are completely rewritten.
Автор: Applebaum, David Название: Levy processes and stochastic calculus ISBN: 0521738652 ISBN-13(EAN): 9780521738651 Издательство: Cambridge Academ Рейтинг: Цена: 13306.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A unique development of these two subjects contained in a single volume. New topics featured in this fully revised edition include regular variation and subexponential distributions, characterisation of Levy processes with finite variation, multiple Wiener-Levy integrals and chaos decomposition, and introductions to Malliavin calculus and stability theory for Levy-driven SDEs.
Описание: Provides an introduction to probability theory and its applications.
Автор: Durrett Название: Essentials of Stochastic Processes ISBN: 331945613X ISBN-13(EAN): 9783319456133 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory.
Автор: Parzen, Emanuel Название: Stochastic processes ISBN: 0898714419 ISBN-13(EAN): 9780898714418 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9656.00 р. Наличие на складе: Нет в наличии.
Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.
Описание: Investigates different deterministic and stochastic error bounds of numerical analysis. This book considers worst case error bounds and their relation to the theory of n-widths. It studies special problems such approximation, optimization, and integration for different function classes. It compares adaptive and nonadaptive methods.
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