Random Iterative Models

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Publisher : Springer Science & Business Media
ISBN 13 : 3662128802
Total Pages : 394 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis Random Iterative Models by : Marie Duflo

Download or read book Random Iterative Models written by Marie Duflo and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, self-contained review of a wide range of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, organizing multi-access broadcast channels, self-learning of neural networks ...). Suitable for mathematicians (researchers and also students) and engineers.

Statistics of Random Processes II

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Publisher : Springer Science & Business Media
ISBN 13 : 3662100282
Total Pages : 409 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis Statistics of Random Processes II by : Robert S. Liptser

Download or read book Statistics of Random Processes II written by Robert S. Liptser and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW

Statistics of Random Processes II

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540639282
Total Pages : 428 pages
Book Rating : 4.6/5 (392 download)

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Book Synopsis Statistics of Random Processes II by : Robert Shevilevich Lipt︠s︡er

Download or read book Statistics of Random Processes II written by Robert Shevilevich Lipt︠s︡er and published by Springer Science & Business Media. This book was released on 2001 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW

Random Walks in the Quarter-Plane

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540650478
Total Pages : 184 pages
Book Rating : 4.6/5 (54 download)

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Book Synopsis Random Walks in the Quarter-Plane by : Guy Fayolle

Download or read book Random Walks in the Quarter-Plane written by Guy Fayolle and published by Springer Science & Business Media. This book was released on 1999-05-04 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Promoting original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries, the authors use Using Riemann surfaces and boundary value problems to propose completely new approaches to solve functional equations of two complex variables. These methods can also be employed to characterize the transient behavior of random walks in the quarter plane.

Iterative Learning Control with Passive Incomplete Information

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Publisher : Springer
ISBN 13 : 9811082677
Total Pages : 294 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Iterative Learning Control with Passive Incomplete Information by : Dong Shen

Download or read book Iterative Learning Control with Passive Incomplete Information written by Dong Shen and published by Springer. This book was released on 2018-04-16 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.—a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model—for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.

Stochastic Integration and Differential Equations

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Publisher : Springer
ISBN 13 : 3662100614
Total Pages : 430 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis Stochastic Integration and Differential Equations by : Philip Protter

Download or read book Stochastic Integration and Differential Equations written by Philip Protter and published by Springer. This book was released on 2013-12-21 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has been 15 years since the first edition of Stochastic Integration and Differential Equations, A New Approach appeared, and in those years many other texts on the same subject have been published, often with connections to applications, especially mathematical finance. Yet in spite of the apparent simplicity of approach, none of these books has used the functional analytic method of presenting semimartingales and stochastic integration. Thus a 2nd edition seems worthwhile and timely, though it is no longer appropriate to call it "a new approach". The new edition has several significant changes, most prominently the addition of exercises for solution. These are intended to supplement the text, but lemmas needed in a proof are never relegated to the exercises. Many of the exercises have been tested by graduate students at Purdue and Cornell Universities. Chapter 3 has been completely redone, with a new, more intuitive and simultaneously elementary proof of the fundamental Doob-Meyer decomposition theorem, the more general version of the Girsanov theorem due to Lenglart, the Kazamaki-Novikov criteria for exponential local martingales to be martingales, and a modern treatment of compensators. Chapter 4 treats sigma martingales (important in finance theory) and gives a more comprehensive treatment of martingale representation, including both the Jacod-Yor theory and Emery’s examples of martingales that actually have martingale representation (thus going beyond the standard cases of Brownian motion and the compensated Poisson process). New topics added include an introduction to the theory of the expansion of filtrations, a treatment of the Fefferman martingale inequality, and that the dual space of the martingale space H^1 can be identified with BMO martingales. Solutions to selected exercises are available at the web site of the author, with current URL http://www.orie.cornell.edu/~protter/books.html.

Large Deviations Techniques and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3642033113
Total Pages : 396 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Large Deviations Techniques and Applications by : Amir Dembo

Download or read book Large Deviations Techniques and Applications written by Amir Dembo and published by Springer Science & Business Media. This book was released on 2009-11-03 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large deviation estimates have proved to be the crucial tool required to handle many questions in statistics, engineering, statistial mechanics, and applied probability. Amir Dembo and Ofer Zeitouni, two of the leading researchers in the field, provide an introduction to the theory of large deviations and applications at a level suitable for graduate students. The mathematics is rigorous and the applications come from a wide range of areas, including electrical engineering and DNA sequences. The second edition, printed in 1998, included new material on concentration inequalities and the metric and weak convergence approaches to large deviations. General statements and applications were sharpened, new exercises added, and the bibliography updated. The present soft cover edition is a corrected printing of the 1998 edition.

Numerical Solution of Stochastic Differential Equations

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Publisher : Springer Science & Business Media
ISBN 13 : 3662126168
Total Pages : 666 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis Numerical Solution of Stochastic Differential Equations by : Peter E. Kloeden

Download or read book Numerical Solution of Stochastic Differential Equations written by Peter E. Kloeden and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: The numerical analysis of stochastic differential equations (SDEs) differs significantly from that of ordinary differential equations. This book provides an easily accessible introduction to SDEs, their applications and the numerical methods to solve such equations. From the reviews: "The authors draw upon their own research and experiences in obviously many disciplines... considerable time has obviously been spent writing this in the simplest language possible." --ZAMP

Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

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Publisher : Springer Nature
ISBN 13 : 3030986616
Total Pages : 1981 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging by : Ke Chen

Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by Springer Nature. This book was released on 2023-02-24 with total page 1981 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.

Stochastic Portfolio Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 1475736991
Total Pages : 190 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Stochastic Portfolio Theory by : E. Robert Fernholz

Download or read book Stochastic Portfolio Theory written by E. Robert Fernholz and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic portfolio theory is a mathematical methodology for constructing stock portfolios and for analyzing the effects induced on the behavior of these portfolios by changes in the distribution of capital in the market. Stochastic portfolio theory has both theoretical and practical applications: as a theoretical tool it can be used to construct examples of theoretical portfolios with specified characteristics and to determine the distributional component of portfolio return. This book is an introduction to stochastic portfolio theory for investment professionals and for students of mathematical finance. Each chapter includes a number of problems of varying levels of difficulty and a brief summary of the principal results of the chapter, without proofs.

Fundamentals of Queueing Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 9780387951669
Total Pages : 512 pages
Book Rating : 4.9/5 (516 download)

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Book Synopsis Fundamentals of Queueing Networks by : Hong Chen

Download or read book Fundamentals of Queueing Networks written by Hong Chen and published by Springer Science & Business Media. This book was released on 2001-06-15 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The selection of materials is well balanced in breadth and depth, making the book an ideal graduate-level text for students in engineering, business, applied mathematics, and probability and statistics.

Iterative Learning Control for Systems with Iteration-Varying Trial Lengths

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Publisher : Springer
ISBN 13 : 9811361363
Total Pages : 256 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Iterative Learning Control for Systems with Iteration-Varying Trial Lengths by : Dong Shen

Download or read book Iterative Learning Control for Systems with Iteration-Varying Trial Lengths written by Dong Shen and published by Springer. This book was released on 2019-01-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerous intuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.

R for Data Science

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques

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Publisher : IGI Global
ISBN 13 : 1466601299
Total Pages : 464 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Computational Methods for Optimizing Manufacturing Technology: Models and Techniques by : Davim, J. Paulo

Download or read book Computational Methods for Optimizing Manufacturing Technology: Models and Techniques written by Davim, J. Paulo and published by IGI Global. This book was released on 2012-02-29 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application"--Provided by publisher.

Random Sample Consensus

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Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 155 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Random Sample Consensus by : Fouad Sabry

Download or read book Random Sample Consensus written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-04-30 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Random Sample Consensus Random sample consensus, also known as RANSAC, is an iterative method that is used to estimate the parameters of a mathematical model based on a collection of observed data that includes outliers. This method is used in situations where the outliers are permitted to have no impact on the values of the estimates. The conclusion is that it is also possible to view it as a tool for detecting outliers. An algorithm is considered to be non-deterministic if it is able to generate a suitable result only with a certain probability, and this likelihood increases as the number of iterations that are permitted via the method increases. In 1981, Fischler and Bolles, who were working at SRI International, were the ones who initially published the algorithm. In order to solve the Location Determination Problem (LDP), which is a problem in which the objective is to find the points in space that project onto an image and then convert those points into a set of landmarks with known positions, they utilized RANSAC. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Random sample consensus Chapter 2: Estimator Chapter 3: Least squares Chapter 4: Outlier Chapter 5: Cross-validation (statistics) Chapter 6: Errors and residuals Chapter 7: Mixture model Chapter 8: Robust statistics Chapter 9: Image stitching Chapter 10: Resampling (statistics) (II) Answering the public top questions about random sample consensus. (III) Real world examples for the usage of random sample consensus in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Random Sample Consensus.

Stochastic Modeling and Mathematical Statistics

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Publisher : CRC Press
ISBN 13 : 1466560479
Total Pages : 622 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Stochastic Modeling and Mathematical Statistics by : Francisco J. Samaniego

Download or read book Stochastic Modeling and Mathematical Statistics written by Francisco J. Samaniego and published by CRC Press. This book was released on 2014-01-14 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well

Further Topics on Discrete-Time Markov Control Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 1461205611
Total Pages : 286 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Further Topics on Discrete-Time Markov Control Processes by : Onesimo Hernandez-Lerma

Download or read book Further Topics on Discrete-Time Markov Control Processes written by Onesimo Hernandez-Lerma and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes, the text is mainly confined to MCPs with Borel state and control spaces. Although the book follows on from the author's earlier work, an important feature of this volume is that it is self-contained and can thus be read independently of the first. The control model studied is sufficiently general to include virtually all the usual discrete-time stochastic control models that appear in applications to engineering, economics, mathematical population processes, operations research, and management science.