Markov chain and mixing times, Levin D.A., Peres Y., Wilmer E.L.
Автор: Gamerman, Dani. Название: Markov Chain Monte Carlo ISBN: 1584885874 ISBN-13(EAN): 9781584885870 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.
Описание: Advances in Industrial Mixing is a companion volume and update to the Handbook of Industrial Mixing. The second volume fills in gaps for a number of industries that were not covered in the first edition. Significant changes in five of the fundamental areas are covered in entirely updated or new chapters.
Автор: Richard Boucherie; Nico M van Dijk Название: Markov Decision Processes in Practice ISBN: 3319477641 ISBN-13(EAN): 9783319477640 Издательство: Springer Рейтинг: Цена: 30745.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach.
Автор: David R. Westhead; M. S. Vijayabaskar Название: Hidden Markov Models ISBN: 1493967517 ISBN-13(EAN): 9781493967513 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology.
Автор: L. C. G. Rogers Название: Diffusions, Markov Processes and Martingales ISBN: 0521775930 ISBN-13(EAN): 9780521775939 Издательство: Cambridge Academ Рейтинг: Цена: 11563.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This celebrated volume gives an accessible introduction to stochastic integrals, stochastic differential equations, excursion theory and the general theory of processes. Together with its companion, it helps equip graduate students for research into a subject of great intrinsic interest and wide application.
Описание: This book introduces a new Markov chain optimization method with braking the detailed balance. It develops a quantum Monte Carlo method for nonconserved particles and combines it with the excitation level analysis.
Описание: This brief broadens readers` understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS).
Автор: Banisch, Sven Название: Markov chain aggregation for agent-based models ISBN: 3319248758 ISBN-13(EAN): 9783319248752 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible.
Автор: Marcus Название: Markov Processes, Gaussian Processes, and Local Times ISBN: 1107403758 ISBN-13(EAN): 9781107403758 Издательство: Cambridge Academ Рейтинг: Цена: 12038.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Two foremost researchers present important advances in stochastic process theory by linking well-understood (Gaussian) and less well-understood (Markov) classes of processes. It builds to this material through `mini-courses` on the relevant ingredients, which assume only measure-theoretic probability. This original, readable 2006 book is for researchers and advanced graduate students.
Описание: This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance). .
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