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Dynamic Probabilistic Systems Volume I
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Book Synopsis Dynamic Probabilistic Systems, Volume I by : Ronald A. Howard
Download or read book Dynamic Probabilistic Systems, Volume I written by Ronald A. Howard and published by Courier Corporation. This book was released on 2007-06-05 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated work in two volumes, this text teaches readers to formulate, analyze, and evaluate Markov models. The first volume treats basic process; the second, semi-Markov and decision processes. 1971 edition.
Book Synopsis Dynamic Probabilistic Systems, Volume II by : Ronald A. Howard
Download or read book Dynamic Probabilistic Systems, Volume II written by Ronald A. Howard and published by Courier Corporation. This book was released on 2013-01-18 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, continues his treatment from Volume I with surveys of the discrete- and continuous-time semi-Markov processes, continuous-time Markov processes, and the optimization procedure of dynamic programming. The final chapter reviews the preceding material, focusing on the decision processes with discussions of decision structure, value and policy iteration, and examples of infinite duration and transient processes. Volume II concludes with an appendix listing the properties of congruent matrix multiplication.
Book Synopsis Dynamic Probabilistic Systems, Volume I by : Ronald A. Howard
Download or read book Dynamic Probabilistic Systems, Volume I written by Ronald A. Howard and published by Courier Corporation. This book was released on 2012-05-04 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, begins with the basic Markov model, proceeding to systems analyses of linear processes and Markov processes, transient Markov processes and Markov process statistics, and statistics and inference. Subsequent chapters explore recurrent events and random walks, Markovian population models, and time-varying Markov processes. Volume I concludes with a pair of helpful indexes.
Book Synopsis Dynamic Probabilistic Systems: Markov models by : Ronald A. Howard
Download or read book Dynamic Probabilistic Systems: Markov models written by Ronald A. Howard and published by . This book was released on 1971 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Decision Processes in Dynamic Probabilistic Systems by : A.V. Gheorghe
Download or read book Decision Processes in Dynamic Probabilistic Systems written by A.V. Gheorghe and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Et moi - ... - si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais point aile: human race. It has put common sense back where it belongs. on the topmost shelf next Jules Verne (0 the dusty canister labelled 'discarded non sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Book Synopsis Dynamic probabilistic systems by : Ronald A. Howard
Download or read book Dynamic probabilistic systems written by Ronald A. Howard and published by . This book was released on 1971 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Markov Models written by and published by . This book was released on 1971 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Decision Processes in Dynamic Probabilistic Systems by : A V Gheorghe
Download or read book Decision Processes in Dynamic Probabilistic Systems written by A V Gheorghe and published by . This book was released on 1990-07-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Probabilistic Systems with Continuous Parameter Markov Chains and Semi-Markov Processes by :
Download or read book Dynamic Probabilistic Systems with Continuous Parameter Markov Chains and Semi-Markov Processes written by and published by . This book was released on 1973 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probabilistic Models for Dynamical Systems by : Haym Benaroya
Download or read book Probabilistic Models for Dynamical Systems written by Haym Benaroya and published by CRC Press. This book was released on 2013-05-02 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing equations.Introduces probabilistic modeling and explo
Book Synopsis Reliability Analysis of Dynamic Systems by : Bin Wu
Download or read book Reliability Analysis of Dynamic Systems written by Bin Wu and published by Academic Press. This book was released on 2013-06-19 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring aerospace examples and applications, Reliability Analysis of Dynamic Systems presents the very latest probabilistic techniques for accurate and efficient dynamic system reliability analysis. While other books cover more broadly the reliability techniques and challenges related to large systems, Dr Bin Wu presents a focused discussion of new methods particularly relevant to the reliability analysis of large aerospace systems under harmonic loads in the low frequency range. Developed and written to help you respond to challenges such as non-linearity of the failure surface, intensive computational costs and complexity in your dynamic system, Reliability Analysis of Dynamic Systems is a specific, detailed and application-focused reference for engineers, researchers and graduate students looking for the latest modeling solutions. The Shanghai Jiao Tong University Press Aerospace Series publishes titles that cover the latest advances in research and development in aerospace. Its scope includes theoretical studies, design methods, and real-world implementations and applications. The readership for the series is broad, reflecting the wide range of aerospace interest and application, but focuses on engineering. Forthcoming titles in the Shanghai Jiao Tong University Press Aerospace Series: Reliability Analysis of Dynamic Systems • Wake Vortex Control • Aeroacoustics: Fundamentals and Applications in Aeropropulsion Systems • Computational Intelligence in Aerospace Design • Unsteady Flow and Aeroelasticity in Turbomachinery Authored by a leading figure in Chinese aerospace with 20 years’ professional experience in reliability analysis and engineering simulation. Offers solutions to the challenges of non-linearity, intensive computational cost and complexity in reliability assessment. Aerospace applications and examples used throughout to illustrate accuracy and efficiency achieved with new methods.
Book Synopsis Random Dynamical Systems by : Ludwig Arnold
Download or read book Random Dynamical Systems written by Ludwig Arnold and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first systematic presentation of the theory of dynamical systems under the influence of randomness, this book includes products of random mappings as well as random and stochastic differential equations. The basic multiplicative ergodic theorem is presented, providing a random substitute for linear algebra. On its basis, many applications are detailed. Numerous instructive examples are treated analytically or numerically.
Book Synopsis Handbook of Dynamics and Probability by : Peter Müller
Download or read book Handbook of Dynamics and Probability written by Peter Müller and published by Springer Nature. This book was released on 2021-11-20 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our time is characterized by an explosive growth in the use of ever more complicated and sophisticated (computer) models. These models rely on dynamical systems theory for the interpretation of their results and on probability theory for the quantification of their uncertainties. A conscientious and intelligent use of these models requires that both these theories are properly understood. This book is to provide such understanding. It gives a unifying treatment of dynamical systems theory and probability theory. It covers the basic concepts and statements of these theories, their interrelations, and their applications to scientific reasoning and physics. The book stresses the underlying concepts and mathematical structures but is written in a simple and illuminating manner without sacrificing too much mathematical rigor. The book is aimed at students, post-docs, and researchers in the applied sciences who aspire to better understand the conceptual and mathematical underpinnings of the models that they use. Despite the peculiarities of any applied science, dynamics and probability are the common and indispensable tools in any modeling effort. The book is self-contained, with many technical aspects covered in appendices, but does require some basic knowledge in analysis, linear algebra, and physics. Peter Müller, now a professor emeritus at the University of Hawaii, has worked extensively on ocean and climate models and the foundations of complex system theories.
Book Synopsis Formal Verification of Probabilistic Systems by : Luca De Alfaro
Download or read book Formal Verification of Probabilistic Systems written by Luca De Alfaro and published by . This book was released on 1998 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents methods for the formal modeling and specification of probabilistic systems, and algorithms for the automated verification of these systems. Our system models describe the behavior of a system in terms of probability, nondeterminism, fairness and time.
Book Synopsis Dynamic Probabilistic Systems: Semi-Markov and decision processes by : Ronald A. Howard
Download or read book Dynamic Probabilistic Systems: Semi-Markov and decision processes written by Ronald A. Howard and published by John Wiley & Sons. This book was released on 1971 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Probabilistic Models and Social Structure by : Guillermo L. Gómez M.
Download or read book Dynamic Probabilistic Models and Social Structure written by Guillermo L. Gómez M. and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical models have been very successful in the study of the physical world. Galilei and Newton introduced point particles moving without friction under the action of simple forces as the basis for the description of concrete motions like the ones of the planets. This approach was sustained by appro priate mathematical methods, namely infinitesimal calculus, which was being developed at that time. In this way classical analytical mechanics was able to establish some general results, gaining insight through explicit solution of some simple cases and developing various methods of approximation for handling more complicated ones. Special relativity theory can be seen as an extension of this kind of modelling. In the study of electromagnetic phenomena and in general relativity another mathematical model is used, in which the concept of classical field plays the fundamental role. The equations of motion here are partial differential equations, and the methods of study used involve further developments of classical analysis. These models are deterministic in nature. However it was realized already in the second half of last century, through the work of Maxwell, Boltzmann, Gibbs and others, that in the discussion of systems involving a great number of particles, the deterministic description is not by itself of great help, in particu lar a suitable "weighting" of all possible initial conditions should be considered.
Book Synopsis Practical Probabilistic Programming by : Avi Pfeffer
Download or read book Practical Probabilistic Programming written by Avi Pfeffer and published by Simon and Schuster. This book was released on 2016-03-29 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to model application domains and then express those probabilistic models in code. Although PP can seem abstract, in this book you'll immediately work on practical examples, like using the Figaro language to build a spam filter and applying Bayesian and Markov networks, to diagnose computer system data problems and recover digital images. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The data you accumulate about your customers, products, and website users can help you not only to interpret your past, it can also help you predict your future! Probabilistic programming uses code to draw probabilistic inferences from data. By applying specialized algorithms, your programs assign degrees of probability to conclusions. This means you can forecast future events like sales trends, computer system failures, experimental outcomes, and many other critical concerns. About the Book Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In this book, you’ll immediately work on practical examples like building a spam filter, diagnosing computer system data problems, and recovering digital images. You’ll discover probabilistic inference, where algorithms help make extended predictions about issues like social media usage. Along the way, you’ll learn to use functional-style programming for text analysis, object-oriented models to predict social phenomena like the spread of tweets, and open universe models to gauge real-life social media usage. The book also has chapters on how probabilistic models can help in decision making and modeling of dynamic systems. What's Inside Introduction to probabilistic modeling Writing probabilistic programs in Figaro Building Bayesian networks Predicting product lifecycles Decision-making algorithms About the Reader This book assumes no prior exposure to probabilistic programming. Knowledge of Scala is helpful. About the Author Avi Pfeffer is the principal developer of the Figaro language for probabilistic programming. Table of Contents PART 1 INTRODUCING PROBABILISTIC PROGRAMMING AND FIGARO Probabilistic programming in a nutshell A quick Figaro tutorial Creating a probabilistic programming application PART 2 WRITING PROBABILISTIC PROGRAMS Probabilistic models and probabilistic programs Modeling dependencies with Bayesian and Markov networks Using Scala and Figaro collections to build up models Object-oriented probabilistic modeling Modeling dynamic systems PART 3 INFERENCE The three rules of probabilistic inference Factored inference algorithms Sampling algorithms Solving other inference tasks Dynamic reasoning and parameter learning
