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by Analytic Sciences Corporation

Analytic_Sciences_Corporation Mathematics English

Mathematics

Author:

Analytic Sciences Corporation
ISBN:

0262200279
ISBN13:

978-0262200271
Genre:

Science / Math
Publisher:

M.I.T. Press (1974)
Pages:

374 pages
Subcategory:

Mathematics
Language:

English
FB2 format

1867 kb
ePUB format

1341 kb
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1867 kb
Rating:

4.4
Votes:

647
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ISBN-13: 978-0262570480. Only 6 left in stock (more on the way).

This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the .

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.

Applied Optimal Estimation (MIT Press). The Analytic Sciences Corporation. ISBN 10: 0262570483 ISBN 13: 9780262570480. 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.

The intent of this book is to enable readers to achieve a level of competence that will permit their participation in the deslgn and evaluation of practical estimators. Therefore, the text is oriented to the applied rather than theoretical aspects of optimal estimation.

This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more . The work is the product of the technical staff of the 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 systemsArthur 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.

In applied statistics, optimal estimation is a regularized matrix inverse method based on Bayes' theorem. It is used very commonly in the geosciences, particularly for atmospheric sounding. A matrix inverse problem looks like this: The essential concept is to transform the matrix, A, into a conditional probability and the variables, and. into probability distributions by assuming Gaussian statistics and using ed covariance matrices.

A bottom-up approach that enables readers to master and apply the latest techniques in state estimationThis book offers the best mathematical approaches to estimating the state of a general system.

A Closed-Form Analytical Solution for Optimal Coordination of Connected and Automated Vehicles.

Control: Optimization, Estimation, and. Control-Arthur. This chapter is devoted to the estimation of nondeterministic quantities with special focus being on estimation of the state of a dynamic system, . the location and orientation of a mobile robot, and also estimation of the coordinates of a detected object of interest. A Closed-Form Analytical Solution for Optimal Coordination of Connected and Automated Vehicles.

Applied Optimal Control: Optimization, Estimation and Control. Applied Optimal Control: Optimization, Estimation, And Control. Quantum State Estimation. Nonlinear Parameter Estimation.

Rent Applied Optimal Estimation at Chegg. Author Gelb, Arthur,, Analytical Sciences Corp-Technical Staff. ISBN13: 9780262570480. com and save up to 80% off list price and 90% off used textbooks. More Books . ABOUT CHEGG.

Lynnak

My first assignment out of grad school involved inertial, celestial, satellite navigation systems, the obvious task for which the Kalman filter was developed. However, that was 1962, and Kalman's papers on filtering were published in 1960 and 1961. Those working such problems typically came from an electrical engineering background. Like most at the time, I couldn't read Kalman's papers, which required one to read sentences of matrices, and understand noise and random processes. In 1973 I returned to grad school to pursue a doctorate in control theory. The second semester I took out Kalman's papers, and re-derived his work. My graduate advisor had been a student with Kalman at Columbia, and had been a teacher of Gelb there. The following year I was doing covariance analysis on astrodynamics systems. My advisor recommended Gelb's book to me, so I read it, re-derived all the material, worked all the problems in the book, and built a career analyzing systems with these methods, and then taught the material at the University of Colorado using this book. At one time I was asked to join the authors at TASC, working on the navigation systems that I started with years earlier.

There is a wealth of new literature available, in particular on particle filters and unscented filters, and more recent books cover such topics.But without a doubt, this is still the best beginning text on the subject.

Although this book is forty years old, it is the best tutorial available. A reader can then turn to other sources for newer developments.

Felhann

This is a classic and excellent introduction to modern filtering and probably theory. It is written for the first practitioners of estimation and contains material that modern books dont have.

Tygokasa

This is the defintive source for estimation algorithms. It is easy to understand and makes it easy to derive your own estimation system equations for tracking and prediction. Developing systems from the information provided in this book has made me a believer in statistics and an admirer of JCF Gauss.

Tekasa

This book should be a great reference for all engineering students who are dealing with dynamic systems, at entry level. Moderate advanced mathematics being involved, the book provides clear and straightforward discussion for a variety of estimation techniques. Moreover, I like the examples contained very much, since they offer you hand-on experience for understanding the techniques better.

LONUDOG

I knew almost nothing about estimation and Kalman filters before reading this book. I have not finished reading it, but so far this book seems to be the best introduction to the field that I have been able to get my hands on.

Kiutondyl

Having read most of the books with "Kalman Filter" in the title I had come to the conclusion that their aim was to give practitioners a pat on the back for understanding the black art of their craft, not to help others to understand it. Then I read some reviews of this book and thought I'd give it a try. It is not "Kalman Filters for Dummies" or anything for dummies, you still need a good grasp of mathematics to read it, but it really aims to educate and bring clarity to the subject of estimation and estimators. Something of a hidden classic it is well worth it's modest price. I would have given it five stars except for the somewhat archaic layout and small print, but I would hate to see an updated reprint that made any changes to the excellent content.

Anicasalar

This is a great textbook. Material is explained very well with clear terms without exeeding with mathematics.

this book is not only cheap! but is also a very good reference book. It might not be very reader friendly at the beginning, but if you have a sort of background it is ok.

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