Random Processes in Automatic Control PDF Download
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Author: J. Halcombe Laning
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages : 456
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Book Description
Author: J. Halcombe Laning
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages : 456
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Book Description
Author: R.S. Liptser
Publisher: Springer Science & Business Media
ISBN: 1475716656
Category : Mathematics
Languages : en
Pages : 405
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Book Description
A considerable number of problems in the statistics of random processes are formulated within the following scheme. On a certain probability space (Q, ff, P) a partially observable random process (lJ,~) = (lJ ~/), t :;::-: 0, is given with only the second component n ~ = (~/), t:;::-: 0, observed. At any time t it is required, based on ~h = g., ° s sst}, to estimate the unobservable state lJ/. This problem of estimating (in other words, the filtering problem) 0/ from ~h will be discussed in this book. It is well known that if M(lJ;)
Author: R.S. Liptser
Publisher: Springer Science & Business Media
ISBN: 1475742932
Category : Mathematics
Languages : en
Pages : 348
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Book Description
Author: Bruce Hajek
Publisher: Cambridge University Press
ISBN: 1316241246
Category : Technology & Engineering
Languages : en
Pages : 429
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Book Description
This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms. Key topics covered include: • Calculus of random processes in linear systems • Kalman and Wiener filtering • Hidden Markov models for statistical inference • The estimation maximization (EM) algorithm • An introduction to martingales and concentration inequalities. Understanding of the key concepts is reinforced through over 100 worked examples and 300 thoroughly tested homework problems (half of which are solved in detail at the end of the book).
Author: Igor N. Kovalenko
Publisher: CRC Press
ISBN: 9780849328701
Category : Mathematics
Languages : en
Pages : 456
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Book Description
Devising and investigating random processes that describe mathematical models of phenomena is a major aspect of probability theory applications. Stochastic methods have penetrated into an unimaginably wide scope of problems encountered by researchers who need stochastic methods to solve problems and further their studies. This handbook supplies the knowledge you need on the modern theory of random processes. Packed with methods, Models of Random Processes: A Handbook for Mathematicians and Engineers presents definitions and properties on such widespread processes as Poisson, Markov, semi-Markov, Gaussian, and branching processes, and on special processes such as cluster, self-exiting, double stochastic Poisson, Gauss-Poisson, and extremal processes occurring in a variety of different practical problems. The handbook is based on an axiomatic definition of probability space, with strict definitions and constructions of random processes. Emphasis is placed on the constructive definition of each class of random processes, so that a process is explicitly defined by a sequence of independent random variables and can easily be implemented into the modelling. Models of Random Processes: A Handbook for Mathematicians and Engineers will be useful to researchers, engineers, postgraduate students and teachers in the fields of mathematics, physics, engineering, operations research, system analysis, econometrics, and many others.
Author: D. K. Bowser
Publisher:
ISBN:
Category : Airplanes
Languages : en
Pages : 56
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Book Description
The digital simulation of terrain or longitudinal gust profiles is shown to be practical. Its use as input to an overall system simulation has reasonable promise of success. With the tools developed in this report, the user has at his disposal a means of determining what is a reasonable choice for the numerical integration increment and what is a sufficient sample length in a statistical sense.
Author: Franklin Institute (Philadelphia, Pa.)
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 636
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Book Description
Vols. 1-69 include more or less complete patent reports of the U. S. Patent Office for years 1825-1859. cf. Index to v. 1-120 of the Journal, p. [415]
Author: V. A. Ogorodnikov
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110941996
Category : Mathematics
Languages : en
Pages : 252
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Book Description
No detailed description available for "Numerical Modelling of Random Processes and Fields".
Author: A. A. Sveshnikov
Publisher: Elsevier
ISBN: 1483222632
Category : Mathematics
Languages : en
Pages : 332
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Book Description
International Series of Monographs in Pure and Applied Mathematics, Volume 89: Applied Methods of the Theory of Random Functions presents methods of random functions analysis with their applications in various branches of technology, such as in the theory of ships, automatic regulation and control, and radio engineering. This book discusses the general properties of random functions, spectral theory of stationary random functions, and determination of optimal dynamical systems. The experimental methods for the determination of characteristics of random functions, method of envelopes, and some supplementary problems of the theory of random functions are also deliberated. This publication is intended for engineers and scientists who use the methods of the theory of probability in various branches of technology.
Author: Andrew H. Jazwinski
Publisher: Courier Corporation
ISBN: 0486318192
Category : Science
Languages : en
Pages : 404
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Book Description
This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.
