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Graph Directed Markov Systems, R. Daniel Mauldin



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Цена: 9433р.
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Склад Англия: 63 шт.  Склад Америка: 134 шт.  
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Автор: R. Daniel Mauldin
Название:  Graph Directed Markov Systems
Издательство: Cambridge Academ
Классификация:
Дифферунциально и интегральное исчисление и математический анализ
Прикладная математика

ISBN: 0521825385
ISBN-13(EAN): 9780521825382
ISBN: 0-521-82538-5
ISBN-13(EAN): 978-0-521-82538-2
Обложка/Формат: Hardback
Страницы: 294
Вес: 0.541 кг.
Дата издания: 07.08.2003
Серия: Cambridge Tracts in Mathematics
Язык: English
Размер: 235 x 161 x 23
Читательская аудитория: Professional & vocational
Подзаголовок: Geometry and dynamics of limit sets
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: The main focus of this book is the exploration of the geometric and dynamic properties of a far reaching generalization of a conformal iterated function system - a Graph Directed Markov System. These systems are very robust in that they apply to many settings that do not fit into the scheme of conformal iterated systems. The basic theory is laid out here and the authors have touched on many natural questions arising in its context. However, they also emphasise the many issues and current research topics which can be found in original papers. For example the detailed analysis of the structure of harmonic measures of limit sets, the examination of the doubling property of conformal measures, the extensive study of generalized polynomial like mapping or multifractal analysis of geometrically finite Kleinian groups. This book leads readers onto frontier research in the field, making it ideal for both established researchers and graduate students.
Дополнительное описание: Subject: Mathematics / Abstract Analysis and Probability Theory
Readership: mathematical analysis, dynamical systems
Level: academic researchers, graduate students
Format: 228 x 152 mm 294pp
Chapter Titles: Introduction; 1. Symbolic dynamics; 3. Holder families of functions; 4. Conformal graph directed Markov systems; 5. Examples of graph directed Markov systems; 6. Conformal iterated function systems; 7. Dynamical rigidity of conformal iterated function systems; 8. Parabolic iterated function systems; 9. Parabolic systems: Hausdorff and packing measures.





Diffusions, Markov Processes and Martingales

Автор: L. C. G. Rogers
Название: Diffusions, Markov Processes and Martingales
ISBN: 0521775930 ISBN-13(EAN): 9780521775939
Издательство: Cambridge Academ
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Цена: 6901 р.
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Описание: Now available in paperback, this celebrated book has been prepared with readers’ needs in mind, remaining a systematic treatment of the subject whilst retaining its vitality. The second volume follows on from the first, concentrating on stochastic integrals, stochastic differential equations, excursion theory and the general theory of processes. Much effort has gone into making these subjects as accessible as possible by providing many concrete examples that illustrate techniques of calculation, and by treating all topics from the ground up, starting from simple cases. Many of the examples and proofs are new; some important calculational techniques appeared for the first time in this book. Together with its companion volume, this book helps equip graduate students for research into a subject of great intrinsic interest and wide application in physics, biology, engineering, finance and computer science.

Continuous-Time Markov Jump Linear Systems

Автор: Costa
Название: Continuous-Time Markov Jump Linear Systems
ISBN: 3642340997 ISBN-13(EAN): 9783642340994
Издательство: Springer
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Цена: 11494 р.
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Описание: Covering an active and high-profile research topic, this volume presents a unified, rigorous treatment of recent developments in control theory that unlock numerous applications in high-integrity systems such as robotics, economics and wireless communications.

Discrete-Time Markov Jump Linear Systems

Автор: Costa O.L.V., Fragoso M.D., Marques R.P.
Название: Discrete-Time Markov Jump Linear Systems
ISBN: 1852337613 ISBN-13(EAN): 9781852337612
Издательство: Springer
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Цена: 14629 р.
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Описание: Safety critical and high-integrity systems, such as industrial plants and economic systems can be subject to abrupt changes - for instance due to component or interconnection failure, and sudden environment changes etc. Combining probability and operator theory, Discrete-Time Markov Jump Linear Systems provides a unified and rigorous treatment of recent results for the control theory of discrete jump linear systems, which are used in these areas of application. The book is designed for experts in linear systems with Markov jump parameters, but is also of interest for specialists in stochastic control since it presents stochastic control problems for which an explicit solution is possible - making the book suitable for course use. From the reviews:"This text is very well written...it may prove valuable to those who work in the area, are at home with its mathematics, and are interested in stability of linear systems, optimal control, and filtering." Journal of the American Statistical Association, December 2005

From markov chains to non-equilibrium particle systems (2nd edition)

Название: From markov chains to non-equilibrium particle systems (2nd edition)
ISBN: 9812388117 ISBN-13(EAN): 9789812388117
Издательство: World Scientific Publishing
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Цена: 19671 р.
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Описание: This book is representative of the work of Chinese probabilists on probability theory and its applications in physics. It presents a unique treatment of general Markov jump processes: uniqueness, various types of ergodicity, Markovian couplings, reversibility, spectral gap, etc. It also deals with a typical class of non-equilibrium particle systems, including the typical Schlogl model taken from statistical physics.

The constructions, ergodicity and phase transitions for this class of Markov interacting particle systems, namely, reaction-diffusion processes, are presented. In this new edition, a large part of the text has been updated and two-and-a-half chapters have been rewritten. The book is self-contained and can be used in a course on stochastic processes for graduate students.

Functional Inequalities Markov Semigroups And Spectral Theory

Автор: Fengyu Wang
Название: Functional Inequalities Markov Semigroups And Spectral Theory
ISBN: 0080449425 ISBN-13(EAN): 9780080449425
Издательство: Elsevier Science
Цена: 9295 р.
Наличие на складе: Невозможна поставка.

Описание: In this book, the functional inequalities are introduced to describe:
(i) the spectrum of the generator: the essential and discrete spectrums, high order eigenvalues, the principle eigenvalue, and the spectral gap;
(ii) the semigroup properties: the uniform intergrability, the compactness, the convergence rate, and the existence of density;
(iii) the reference measure and the intrinsic metric: the concentration, the isoperimetic inequality, and the transportation cost inequality.

Markov Decision Processes in Practice

Автор: Richard Boucherie; Nico M van Dijk
Название: Markov Decision Processes in Practice
ISBN: 3319477641 ISBN-13(EAN): 9783319477640
Издательство: Springer
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Цена: 22989 р.
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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.

Boundary Value Problems and Markov Processes

Автор: Kazuaki Taira
Название: Boundary Value Problems and Markov Processes
ISBN: 3642016766 ISBN-13(EAN): 9783642016769
Издательство: Springer
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Цена: 4701 р.
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Описание: This is a thorough and accessible exposition on the functional analytic approach to the problem of construction of Markov processes with Ventcel` boundary conditions in probability theory. It presents new developments in the theory of singular integrals.

Markov Chains

Автор: Bremaud
Название: Markov Chains
ISBN: 0387985093 ISBN-13(EAN): 9780387985091
Издательство: Springer
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Цена: 5951 р.
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Описание: This book discusses both the theory and applications of Markov chains. The author studies both discrete-time and continuous-time chains and connected topics such as finite Gibbs fields, non-homogeneous Markov chains, discrete time regenerative processes, Monte Carlo simulation, simulated annealing, and queueing networks are also developed in this accessible and self-contained text. The text is firstly an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level. Its primary objective is to initiate the student to the art of stochastic modelling. The treatment is mathematical, with definitions, theorems, proofs and a number of classroom examples which help the student to fully grasp the content of the main results. Problems of varying difficulty are proposed at the close of each chapter. The text is motivated by significant applications and progressively brings the student to the borders of contemporary research. Students and researchers in operations research and electrical engineering as well as in physics, biology and the social sciences will find this book of interest.

Cycle Representations of Markov Processes

Автор: Sophia L. Kalpazidou
Название: Cycle Representations of Markov Processes
ISBN: 1441921214 ISBN-13(EAN): 9781441921215
Издательство: Springer
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Цена: 17241 р.
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Metastability and Markov State Models in Molecular Dynamics

Автор: Schutte Christof
Название: Metastability and Markov State Models in Molecular Dynamics
ISBN: 0821843591 ISBN-13(EAN): 9780821843598
Издательство: Eurospan
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Цена: 4493 р.
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Описание: Applications in modern biotechnology and molecular medicine often require simulation of biomolecular systems in atomic representation with immense length and timescales that are far beyond the capacity of computer power currently available. As a consequence, there is an increasing need for reduced models that describe the relevant dynamical properties while at the same time being less complex. In this book the authors exploit the existence of metastable sets for constructing such a reduced molecular dynamics model, the so-called Markov State Model (MSM), with good approximation properties on the long timescales. With its many examples and illustrations, this book is addressed to graduate students, mathematicians, and practical computational scientists wanting an overview of the mathematical background for the ever increasing research activity on how to construct MSMs for very different molecular systems ranging from peptides to proteins, from RNA to DNA, and via molecular sensors to molecular aggregation. This book bridges the gap between mathematical research on molecular dynamics and its practical use for realistic molecular systems by providing readers with tools for performing in-depth analysis of simulation and data-analysis methods.

Inference in Hidden Markov Models

Автор: Capp?
Название: Inference in Hidden Markov Models
ISBN: 0387402640 ISBN-13(EAN): 9780387402642
Издательство: Springer
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Цена: 18809 р.
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Описание: Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states.In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models.This volume will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The algorithmic parts of the book do not require an advanced mathematical background, while the more theoretical parts require knowledge of probability theory at the measure-theoretical level.From the reviews:"By providing an overall survey of results obtained so far in a very readable manner, and also presenting some new ideas, this well-written book will appeal to academic researchers in the field of HMMs, with PhD students working on related topics included. It will also appeal to practitioners and researchers from other fields by guiding them through the computational steps needed for making inference HMMs and/or by providing them with the relevant underlying statistical theory. In the reviewer's opinion this book will shortly become a reference work in its field." MathSciNet"This monograph is a valuable resource. It provides a good literature review, an excellent account of the state of the art research on the necessary theory and algorithms, and ample illustrations of numerous applications of HMM. It goes much beyond the earlier resources on HMM...I anticipate this work to serve well many Technometrics readers in the coming years." Haikady N. Nagaraja for Technometrics, November 2006

Markov Processes for Stochastic Modeling,

Автор: Oliver Ibe
Название: Markov Processes for Stochastic Modeling,
ISBN: 0124077951 ISBN-13(EAN): 9780124077959
Издательство: Elsevier Science
Цена: 7937 р.
Наличие на складе: Невозможна поставка.


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