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Recent Developments in Fractals and Related Fields (Repost)

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Recent Developments in Fractals and Related Fields (Repost)

Recent Developments in Fractals and Related Fields by Julien Barral
English | PDF | 2010 | 424 Pages | ISBN : 0817648879 | 6.4 MB

This book—an outgrowth of an international conference held in honor of Jacques Peyrière—provides readers with an overview of recent developments in the mathematical fields related to fractals. Included are original research contributions as well as surveys written by experts in their respective fields.

Denumerable Markov Chains: with a chapter of Markov Random Fields by David Griffeath

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Denumerable Markov Chains: with a chapter of Markov Random Fields by David Griffeath

Denumerable Markov Chains: with a chapter of Markov Random Fields by David Griffeath by John G. Kemeny
English | PDF | 1976 | 495 Pages | ISBN : 0387901779 | 36.1 MB

With the first edition out of print, we decided to arrange for republi­ cation of Denumerrible Markov Ohains with additional bibliographic material. The new edition contains a section Additional Notes that indicates some of the developments in Markov chain theory over the last ten years.

Adventures in Stochastic Processes

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Adventures in Stochastic Processes

Adventures in Stochastic Processes by Sidney I. Resnick
English | PDF | 2002 | 640 Pages | ISBN : 0817635912 | 61.1 MB

Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. In a lively and imaginative presentation, studded with examples, exercises, and applications, and supported by inclusion of computational procedures, the author has created a textbook that provides easy access to this fundamental topic for many students of applied sciences at many levels. With its carefully modularized discussion and crystal clear differentiation between rigorous proof and plausibility argument, it is accessible to beginners but flexible enough to serve as well those who come to the course with strong backgrounds.

Foundations of Modern Probability, Third Edition

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Foundations of Modern Probability, Third Edition

Foundations of Modern Probability, Third Edition by Olav Kallenberg
English | PDF | 2021 | 931 Pages | ISBN : 3030618706 | 5.6 MB

This new, thoroughly revised and expanded 3rd edition of a classic gives a comprehensive coverage of modern probability in a single book. It is a truly modern text, providing not only classical results but also material that will be important for future research. Much has been added to the previous edition, including eight entirely new chapters on subjects like random measures, Malliavin calculus, multivariate arrays, and stochastic differential geometry.

Stochastic Control of Hereditary Systems and Applications (Repost)

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Stochastic Control of Hereditary Systems and Applications (Repost)

Stochastic Control of Hereditary Systems and Applications by Mou-Hsiung Chang
English | PDF | 2008 | 418 Pages | ISBN : 0387758054 | 3.1 MB

This research monograph develops the Hamilton-Jacobi-Bellman (HJB) theory through dynamic programming principle for a class of optimal control problems for stochastic hereditary differential systems. It is driven by a standard Brownian motion and with a bounded memory or an infinite but fading memory.

Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications

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Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications

Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications by Xiao-Sheng Si
English | PDF,EPUB | 2017 | 436 Pages | ISBN : 3662540282 | 23.8 MB

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail.

Statistical Theory of Open Systems Volume 1: A Unified Approach to Kinetic Description of Processes in Active Systems

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Statistical Theory of Open Systems Volume 1: A Unified Approach to Kinetic Description of Processes in Active Systems

Statistical Theory of Open Systems Volume 1: A Unified Approach to Kinetic Description of Processes in Active Systems by Yu. L. Klimontovich
English | PDF | 1995 | 589 Pages | ISBN : 0792331990 | 71.07 MB

Let us begin by quoting from the Preface to the author's Statistical Physics (Moscow, Nauka 1982; also published in English by Harwood in 1986): '''My God! Yet another book on statistical physics! There's no room on my bookshelves left!' Such emotionsare quite understandable. Beforejumping to conclusions, however, it would be worthwhile to read the Introduction and look through the table of contents.

Brownian Motion, Martingales, and Stochastic Calculus (Repost)

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Brownian Motion, Martingales, and Stochastic Calculus (Repost)

Brownian Motion, Martingales, and Stochastic Calculus by Jean-François Le Gall
English | EPUB | 2016 | 282 Pages | ISBN : 3319310887 | 4.21 MB

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter.

Stochastic Tools in Mathematics and Science, Second Edition

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Stochastic Tools in Mathematics and Science, Second Edition

Stochastic Tools in Mathematics and Science, Second Edition by Alexandre Chorin
English | True PDF | 2009 | 168 Pages | ISBN : 1441910018 | 2.03 MB

Stochastic Tools in Mathematics and Science is an introductory book on probability-based modeling. It covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. The topics covered include conditional expectations, stochastic processes, Brownian motion and its relation to partial differential equations, Langevin equations, the Liouville and Fokker-Planck equations, as well as Markov chain Monte Carlo algorithms, renormalization and dimensional reduction, and basic equilibrium and non-equilibrium statistical mechanics. The applications include data assimilation, prediction from partial data, spectral analysis, and turbulence. A noteworthy feature of the book is the systematic analysis of memory effects.