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Intro To Optimal Estimation


Intro To Optimal Estimation
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Introduction To Optimal Estimation


Introduction To Optimal Estimation
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Author : Edward W. Kamen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Introduction To Optimal Estimation written by Edward W. Kamen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.


A handy technical introduction to the latest theories and techniques of optimal estimation. It provides readers with extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood and maximum a posteriori estimation based on discrete-time measurements. Much emphasis is placed on how they interrelate and fit together to form a systematic development of optimal estimation. Examples and exercises refer to MATLAB software.



An Introduction To Optimal Estimation Of Dynamical Systems


An Introduction To Optimal Estimation Of Dynamical Systems
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Author : J.L. Junkins
language : en
Publisher: Springer
Release Date : 1978-07-31

An Introduction To Optimal Estimation Of Dynamical Systems written by J.L. Junkins and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978-07-31 with Mathematics categories.


This text 1s designed to introduce the fundamentals of esti mation to engineers, scientists, and applied mathematicians. The level of the presentation should be accessible to senior under graduates and should prove especially well-suited as a self study guide for practicing professionals. My primary motivation for writing this book 1s to make a significant contribution toward minimizing the painful process most newcomers must go through in digesting and applying the theory. Thus the treatment 1s intro ductory and essence-oriented rather than comprehensive. While some original material 1s included, the justification for this text lies not in the contribution of dramatic new theoretical re sults, but rather in the degree of success I believe that I have achieved in providing a source from which this material may be learned more efficiently than through study of an existing text or the rather diffuse literature. This work is the outgrowth of the author's mid-1960's en counter with the subject while motivated by practical problems aSSociated with space vehicle orbit determination and estimation of powered rocket trajectories. The text has evolved as lecture notes for short courses and seminars given to professionals at Pr>efaae various private laboratories and government agencies, and during the past six years, in conjunction with engineering courses taught at the University of Virginia. To motivate the reader's thinking, the structure of a typical estimation problem often assumes the following form: • Given a dynamical system, a mathematical model is hypothesized based upon the experience of the investigator.



Intro To Optimal Estimation


Intro To Optimal Estimation
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Author : P. B. Liebelt
language : en
Publisher:
Release Date : 1967

Intro To Optimal Estimation written by P. B. Liebelt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1967 with categories.




An Introduction To Optimal Estimation


An Introduction To Optimal Estimation
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Author : Paul B. Liebelt
language : en
Publisher:
Release Date : 1967

An Introduction To Optimal Estimation written by Paul B. Liebelt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1967 with Estimation theory categories.




Optimal And Robust Estimation


Optimal And Robust Estimation
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Author : Frank L. Lewis
language : en
Publisher: CRC Press
Release Date : 2017-12-19

Optimal And Robust Estimation written by Frank L. Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Technology & Engineering categories.


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.



Optimal Estimation


Optimal Estimation
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Author : Frank L. Lewis
language : en
Publisher: Wiley-Interscience
Release Date : 1986-04-15

Optimal Estimation written by Frank L. Lewis and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-04-15 with Mathematics categories.


Describes the use of optimal control and estimation in the design of robots, controlled mechanisms, and navigation and guidance systems. Covers control theory specifically for students with minimal background in probability theory. Presents optimal estimation theory as a tutorial with a direct, well-organized approach and a parallel treatment of discrete and continuous time systems. Gives practical examples and computer simulations. Provides enough mathematical rigor to put results on a firm foundation without an overwhelming amount of proofs and theorems.



An Introduction To Optimal Estimation


An Introduction To Optimal Estimation
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Author : P.B. Liebelt
language : es
Publisher:
Release Date : 1967

An Introduction To Optimal Estimation written by P.B. Liebelt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1967 with categories.




Optimal Estimation Of Dynamic Systems


Optimal Estimation Of Dynamic Systems
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Author : John L. Crassidis
language : en
Publisher: CRC Press
Release Date : 2004-04-27

Optimal Estimation Of Dynamic Systems written by John L. Crassidis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-27 with Mathematics categories.


Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals receiv



Applied Optimal Estimation


Applied Optimal Estimation
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Author : The Analytic Sciences Corporation
language : en
Publisher: MIT Press
Release Date : 1974-05-15

Applied Optimal Estimation written by The Analytic Sciences Corporation and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974-05-15 with Computers categories.


This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation. Even so, theoretical and mathematical concepts are introduced and developed sufficiently to make the book a self-contained source of instruction for readers without prior knowledge of the basic principles of the field. The work is the product of the technical staff of The Analytic Sciences Corporation (TASC), an organization whose success has resulted largely from its applications of optimal estimation techniques to a wide variety of real situations involving large-scale systems. Arthur Gelb writes in the Foreword that "It is our intent throughout to provide a simple and interesting picture of the central issues underlying modern estimation theory and practice. Heuristic, rather than theoretically elegant, arguments are used extensively, with emphasis on physical insights and key questions of practical importance." Numerous illustrative examples, many based on actual applications, have been interspersed throughout the text to lead the student to a concrete understanding of the theoretical material. The inclusion of problems with "built-in" answers at the end of each of the nine chapters further enhances the self-study potential of the text. After a brief historical prelude, the book introduces the mathematics underlying random process theory and state-space characterization of linear dynamic systems. The theory and practice of optimal estimation is them presented, including filtering, smoothing, and prediction. Both linear and non-linear systems, and continuous- and discrete-time cases, are covered in considerable detail. New results are described concerning the application of covariance analysis to non-linear systems and the connection between observers and optimal estimators. The final chapters treat such practical and often pivotal issues as suboptimal structure, and computer loading considerations. This book is an outgrowth of a course given by TASC at a number of US Government facilities. Virtually all of the members of the TASC technical staff have, at one time and in one way or another, contributed to the material contained in the work.



Optimal Estimation In Approximation Theory


Optimal Estimation In Approximation Theory
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Author : Charles Michelli
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-22

Optimal Estimation In Approximation Theory written by Charles Michelli and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-22 with Science categories.


The papers in this volume were presented at an International Symposium on Optimal Estimation in Approximation Theory which was held in Freudenstadt, Federal Republic of Germany, September 27-29, 1976. The symposium was sponsored by the IBM World Trade Europe/Middle East/Africa Corporation, Paris, and IBM Germany. On behalf of all the participants we wish to express our appreciation to the spon sors for their generous support. In the past few years the quantification of the notion of com plexity for various important computational procedures (e. g. multi plication of numbers or matrices) has been widely studied. Some such concepts are necessary ingredients in the quest for optimal, or nearly optimal, algorithms. The purpose of this symposium was to present recent results of similar character in the field or ap proximation theory, as well as to describe the algorithms currently being used in important areas of application of approximation theory such as: crystallography, data transmission systems, cartography, reconstruction from x-rays, planning of radiation treatment, optical perception, analysis of decay processes and inertial navigation system control. It was the hope of the organizers that this con frontation of theory and practice would be of benefit to both groups. Whatever success th•~ symposium had is due, in no small part, to the generous and wise scientific counsel of Professor Helmut Werner, to whom the organizers are most grateful. Dr. T. J. Rivlin Dr. P. Schweitzer IBM T. J. Watson Research Center IBM Germany Scientific and Education Programs Yorktown Heights, N. Y.