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Ditemukan 89 dokumen yang sesuai dengan query
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Shanmugan, K. Sam
Random signals : detection, estimation and data analysis/K.sam Shanmugan and A.M.Breipohl
New York: John Wiley & Sons, 1979
621.380 43 SHA r
Buku Teks  Universitas Indonesia Library
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Borovkov, Konstantin
Elements of stochastic modelling
" This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time ... "
New Jersey: World Scientific, 2014
519.23 BOR e
Buku Teks  Universitas Indonesia Library
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Analytical and stochastic modeling techniques and applications : 19th international conference, ASMTA 2012, Grenoble, France, June 4-6, 2012 : proceedings
" This book constitutes the refereed proceedings of the 19th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2012, held in Grenoble, France, in June 2012. The 20 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on queueing systems; networking applications, Markov chains, stochastic modelling ... "
Berlin : Springer-Verlag, 2012
e20410486
eBooks  Universitas Indonesia Library
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King, Alan J.
Modeling with stochastic programming
" While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from ... "
New York: [, Springer], 2012
e20418916
eBooks  Universitas Indonesia Library
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Stochastic analysis and related topics : in honour of Ali Suleyman Ustunel, Paris, June 2010
" Since the early eighties, Ali Suleyman Ustunel has been one of the main contributors to the field of Malliavin calculus. In a workshop held in Paris, June 2010 several prominent researchers gave exciting talks in honor of his 60th birthday. The present volume includes scientific contributions from this workshop. Probability theory is first and foremost aimed at solving real-life problems containing randomness. Markov processes are one of the key tools for modeling that plays a ... "
Berlin: Springer-Verlag, 2012
e20419574
eBooks  Universitas Indonesia Library
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Zili, Mounir, editor
Stochastic differential equations and processes : SAAP, Tunisia, October 7-9, 2010
" Selected papers submitted by participants of the international Conference “Stochastic Analysis and Applied Probability 2010” ( www.saap2010.org ) make up the basis of this volume. The SAAP 2010 was held in Tunisia, from 7-9 October, 2010, and was organized by the “Applied Mathematics & Mathematical Physics” research unit of the preparatory institute to the military academies of Sousse (Tunisia), chaired by Mounir Zili. The papers cover theoretical, numerical and applied aspects of stochastic processes and ... "
Berlin: [Springer-Verlag, ], 2012
e20419577
eBooks  Universitas Indonesia Library
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Chirikjian, Gregory S.
Stochastic models, information theory, and lie groups, volume 2 : analytic methods and modern applications
" The emphasis in both of these volumes is on the use of stochastic, geometric, and group-theoretic concepts in the modeling of physical phenomena. Volume 2 builds on the fundamentals presented in Volume 1, delving deeper into relationships among stochastic geometry, geometric aspects of the theory of communications and coding, multivariate statistical analysis, and error propagation on Lie groups. Extensive exercises, motivating examples, and real-world applications make the work suitable as a textbook for use in ... "
New York: [Springer Science, ], 2012
e20419587
eBooks  Universitas Indonesia Library
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Markov processes for stochastic modeling / Olivier C. Ibe
" 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 ... "
London, UK : Elsevier, 2013
e20427198
eBooks  Universitas Indonesia Library
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Hanson, Floyd B.
Applied stochastic processes and control for Jump-diffusions: modeling, analysis, and computation
" This self-contained, practical, entry-level text integrates the basic principles of applied mathematics, applied probability, and computational science for a clear presentation of stochastic processes and control for jump diffusions in continuous time. The author covers the important problem of controlling these systems and, through the use of a jump calculus construction, discusses the strong role of discontinuous and nonsmooth properties versus random properties in stochastic systems. The book emphasizes modeling and problem solving and presents ... "
Philadelphia: Society for Industrial and Applied Mathematics, 2007
e20450709
eBooks  Universitas Indonesia Library
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Speyer, Jason Lee
Stochastic processes, estimation, and control
" Uncertainty and risk are integral to engineering because real systems have inherent ambiguities that arise naturally or due to our inability to model complex physics. The authors discuss probability theory, stochastic processes, estimation, and stochastic control strategies and show how probability can be used to model uncertainty in control and estimation problems. The material is practical and rich in research opportunities. The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to ... "
Philadelphia: Society for Industrial and Applied Mathematics, 2008
e20450871
eBooks  Universitas Indonesia Library
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