Point Estimation, Stochastic Approximation, and Robust Kalman Filtering

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Publisher :
ISBN 13 :
Total Pages : 25 pages
Book Rating : 4.:/5 (281 download)

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Book Synopsis Point Estimation, Stochastic Approximation, and Robust Kalman Filtering by : Sanjoy K. Mitter

Download or read book Point Estimation, Stochastic Approximation, and Robust Kalman Filtering written by Sanjoy K. Mitter and published by . This book was released on 1993 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Optimal and Robust Estimation

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Publisher : CRC Press
ISBN 13 : 1351837540
Total Pages : 638 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Optimal and Robust Estimation by : Frank L. Lewis

Download or read book Optimal and Robust Estimation written by Frank L. Lewis and published by CRC Press. This book was released on 2017-12-19 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.

Applications and Optimizations of Kalman Filter and Their Variants

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Publisher : BoD – Books on Demand
ISBN 13 : 0854665668
Total Pages : 204 pages
Book Rating : 4.8/5 (546 download)

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Book Synopsis Applications and Optimizations of Kalman Filter and Their Variants by : Asadullah Khalid

Download or read book Applications and Optimizations of Kalman Filter and Their Variants written by Asadullah Khalid and published by BoD – Books on Demand. This book was released on 2024-07-17 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.

Optimal State Estimation

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Publisher : John Wiley & Sons
ISBN 13 : 0470045337
Total Pages : 554 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Optimal State Estimation by : Dan Simon

Download or read book Optimal State Estimation written by Dan Simon and published by John Wiley & Sons. This book was released on 2006-06-19 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

Approximate Kalman Filtering

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Publisher : World Scientific
ISBN 13 : 9789810213596
Total Pages : 248 pages
Book Rating : 4.2/5 (135 download)

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Book Synopsis Approximate Kalman Filtering by : Guanrong Chen

Download or read book Approximate Kalman Filtering written by Guanrong Chen and published by World Scientific. This book was released on 1993 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modeling; ideal well-conditioned matrices in computation and strictly centralized filtering.In practice, however, one or more of the aforementioned conditions may not be satisfied, so that the standard Kalman filtering algorithm cannot be directly used, and hence ?approximate Kalman filtering? becomes necessary. In the last decade, a great deal of attention has been focused on modifying and/or extending the standard Kalman filtering technique to handle such irregular cases. It has been realized that approximate Kalman filtering is even more important and useful in applications.This book is a collection of several tutorial and survey articles summarizing recent contributions to the field, along the line of approximate Kalman filtering with emphasis on both its theoretical and practical aspects.

Stochastic Approximation and Recursive Estimation

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Publisher : American Mathematical Soc.
ISBN 13 : 9780821809068
Total Pages : 252 pages
Book Rating : 4.8/5 (9 download)

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Book Synopsis Stochastic Approximation and Recursive Estimation by : M. B. Nevel'son

Download or read book Stochastic Approximation and Recursive Estimation written by M. B. Nevel'son and published by American Mathematical Soc.. This book was released on 1976-10-01 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to sequential methods of solving a class of problems to which belongs, for example, the problem of finding a maximum point of a function if each measured value of this function contains a random error. Some basic procedures of stochastic approximation are investigated from a single point of view, namely the theory of Markov processes and martingales. Examples are considered of applications of the theorems to some problems of estimation theory, educational theory and control theory, and also to some problems of information transmission in the presence of inverse feedback.

Systems, Models and Feedback: Theory and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 1475722044
Total Pages : 404 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Systems, Models and Feedback: Theory and Applications by : A. Isidori

Download or read book Systems, Models and Feedback: Theory and Applications written by A. Isidori and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is a great honor and privilege to have this opportunity of celebrating the 65th birthday of Professor Antonio Ruberti by holding an International Conference on Systems, Models and Feedback. The conference, and this volume which contains its proceedings, is a tribute to Professor Ruberti in acknowledgement of his major contributions to System Theory, at a time in which this area was emerging and consolidat ing as an independent discipline, his role as a leader of the Italian academic community, his activity in promoting and fostering close scientific relations between Italian and U.S. scholars in Systems and Control. The format of this conference is inspired by a series of seminars initi ated exactly twenty years ago under the direction of Professor Ruberti, in Italy, and Professor R. R. Mohler, in the U.S. By bringing together many authoritative talents from both countries, these seminars were instrumental in promoting the expansion of System Theory in new areas, notably that of Nonlinear Control, and were the key to successful scientific careers for many of the younger attendants.

Kalman Filtering

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Publisher : John Wiley & Sons
ISBN 13 : 111898496X
Total Pages : 639 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Kalman Filtering by : Mohinder S. Grewal

Download or read book Kalman Filtering written by Mohinder S. Grewal and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

Kalman Filtering

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Publisher : John Wiley & Sons
ISBN 13 : 1118210468
Total Pages : 458 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Kalman Filtering by : Mohinder S. Grewal

Download or read book Kalman Filtering written by Mohinder S. Grewal and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department -- to obtain the manual, send an email to [email protected].

Robust Kalman Filtering for Signals and Systems with Large Uncertainties

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Publisher : Springer Science & Business Media
ISBN 13 : 9780817640897
Total Pages : 224 pages
Book Rating : 4.6/5 (48 download)

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Book Synopsis Robust Kalman Filtering for Signals and Systems with Large Uncertainties by : Ian R. Petersen

Download or read book Robust Kalman Filtering for Signals and Systems with Large Uncertainties written by Ian R. Petersen and published by Springer Science & Business Media. This book was released on 1999 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Kalman Filter gives an optimal estimate of the state of the given process based on output measurements. The aim of this text is to cover the theory of robust state estimation for the case in which the process model contains significant uncertainties and non-linearities.

Introduction to Random Signals, Estimation Theory, and Kalman Filtering

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Publisher : Springer Nature
ISBN 13 : 9819980631
Total Pages : 489 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Introduction to Random Signals, Estimation Theory, and Kalman Filtering by : M. Sami Fadali

Download or read book Introduction to Random Signals, Estimation Theory, and Kalman Filtering written by M. Sami Fadali and published by Springer Nature. This book was released on with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Estimation of Location and Scale Via Stochastic Approximation

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Publisher :
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.:/5 (228 download)

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Book Synopsis Robust Estimation of Location and Scale Via Stochastic Approximation by : Daniel Merlyn Goodfellow

Download or read book Robust Estimation of Location and Scale Via Stochastic Approximation written by Daniel Merlyn Goodfellow and published by . This book was released on 1977 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt:

System Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 1461552230
Total Pages : 494 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis System Theory by : Theodore E. Djaferis

Download or read book System Theory written by Theodore E. Djaferis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Theory: Modeling, Analysis and Control contains thirty-three scientific papers covering a wide range of topics in systems and control. These papers have been contributed to a symposium organized to celebrate Sanjoy K. Mitter's 65th birthday. The following research topics are addressed: distributed parameter systems, stochastic control, filtering and estimation, optimization and optimal control, image processing and vision, hierarchical systems and hybrid control, nonlinear systems, and linear systems. Also included are three survey papers on optimization, nonlinear filtering, and nonlinear systems. Recent advances are reported on the behavioral approach to systems, the relationship between differential games and robust control, estimation of diffusion processes, Markov processes, optimal control, hybrid control, stochastic control, spectral estimation, nonconvex quadratic programming, robust control, control algorithms and quantized linear systems. Innovative explorations are carried out on quantum systems from a control theory perspective, option valuation and hedging, three-dimensional medical visualization, computational structure biology image processing, and hierarchical approaches to complex systems, flow control, scheduling and force feedback in fluid mechanics. The contents reflect on past research accomplishments, current research activity, and future research directions in systems and control theory.

Robust Statistics for Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 1108680488
Total Pages : 315 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Robust Statistics for Signal Processing by : Abdelhak M. Zoubir

Download or read book Robust Statistics for Signal Processing written by Abdelhak M. Zoubir and published by Cambridge University Press. This book was released on 2018-11-08 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the benefits of robust statistics for signal processing with this authoritative yet accessible text. The first ever book on the subject, it provides a comprehensive overview of the field, moving from fundamental theory through to important new results and recent advances. Topics covered include advanced robust methods for complex-valued data, robust covariance estimation, penalized regression models, dependent data, robust bootstrap, and tensors. Robustness issues are illustrated throughout using real-world examples and key algorithms are included in a MATLAB Robust Signal Processing Toolbox accompanying the book online, allowing the methods discussed to be easily applied and adapted to multiple practical situations. This unique resource provides a powerful tool for researchers and practitioners working in the field of signal processing.

Securing Critical Infrastructures and Critical Control Systems: Approaches for Threat Protection

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Publisher : IGI Global
ISBN 13 : 1466626909
Total Pages : 450 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Securing Critical Infrastructures and Critical Control Systems: Approaches for Threat Protection by : Laing, Christopher

Download or read book Securing Critical Infrastructures and Critical Control Systems: Approaches for Threat Protection written by Laing, Christopher and published by IGI Global. This book was released on 2012-12-31 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increased use of technology is necessary in order for industrial control systems to maintain and monitor industrial, infrastructural, or environmental processes. The need to secure and identify threats to the system is equally critical. Securing Critical Infrastructures and Critical Control Systems: Approaches for Threat Protection provides a full and detailed understanding of the vulnerabilities and security threats that exist within an industrial control system. This collection of research defines and analyzes the technical, procedural, and managerial responses to securing these systems.

Advanced Kalman Filtering, Least-Squares and Modeling

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Publisher : Jossey-Bass Publishers
ISBN 13 :
Total Pages : 640 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Advanced Kalman Filtering, Least-Squares and Modeling by : Bruce P. Gibbs

Download or read book Advanced Kalman Filtering, Least-Squares and Modeling written by Bruce P. Gibbs and published by Jossey-Bass Publishers. This book was released on 2011-03 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is intended primarily as a handbook for engineers who must design practical systems. It discusses model development in detail so that the reader may design an estimator that meets all application requirements and is robust to modelling assumptions.

Smoothing, Filtering and Prediction

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Publisher : BoD – Books on Demand
ISBN 13 : 9533077522
Total Pages : 290 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Smoothing, Filtering and Prediction by : Garry Einicke

Download or read book Smoothing, Filtering and Prediction written by Garry Einicke and published by BoD – Books on Demand. This book was released on 2012-02-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the classical smoothing, filtering and prediction techniques together with some more recently developed embellishments for improving performance within applications. It aims to present the subject in an accessible way, so that it can serve as a practical guide for undergraduates and newcomers to the field. The material is organised as a ten-lecture course. The foundations are laid in Chapters 1 and 2, which explain minimum-mean-square-error solution construction and asymptotic behaviour. Chapters 3 and 4 introduce continuous-time and discrete-time minimum-variance filtering. Generalisations for missing data, deterministic inputs, correlated noises, direct feedthrough terms, output estimation and equalisation are described. Chapter 5 simplifies the minimum-variance filtering results for steady-state problems. Observability, Riccati equation solution convergence, asymptotic stability and Wiener filter equivalence are discussed. Chapters 6 and 7 cover the subject of continuous-time and discrete-time smoothing. The main fixed-lag, fixed-point and fixed-interval smoother results are derived. It is shown that the minimum-variance fixed-interval smoother attains the best performance. Chapter 8 attends to parameter estimation. As the above-mentioned approaches all rely on knowledge of the underlying model parameters, maximum-likelihood techniques within expectation-maximisation algorithms for joint state and parameter estimation are described. Chapter 9 is concerned with robust techniques that accommodate uncertainties within problem specifications. An extra term within Riccati equations enables designers to trade-off average error and peak error performance. Chapter 10 rounds off the course by applying the afore-mentioned linear techniques to nonlinear estimation problems. It is demonstrated that step-wise linearisations can be used within predictors, filters and smoothers, albeit by forsaking optimal performance guarantees.