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Optimal State Estimation : Kalman, H Infinity, And Nonlinear Approaches, Hard...

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Book Title
Optimal State Estimation : Kalman, H Infinity, And Nonlinear Appr
ISBN
9780471708582
Publication Year
2006
Type
Textbook
Format
Hardcover
Language
English
Publication Name
Optimal State Estimation : Kalman, H Infinity, and Nonlinear Approaches
Item Height
1.4in
Author
Dan Simon
Item Length
10.3in
Publisher
Wiley & Sons, Incorporated, John
Item Width
7.3in
Item Weight
41.4 Oz
Number of Pages
552 Pages

關於產品

Product Information

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-based source code that corresponds to examples in the book, available on the authors 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 readers 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. A solutions manual is available for instructors. 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.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471708585
ISBN-13
9780471708582
eBay Product ID (ePID)
52323878

Product Key Features

Author
Dan Simon
Publication Name
Optimal State Estimation : Kalman, H Infinity, and Nonlinear Approaches
Format
Hardcover
Language
English
Publication Year
2006
Type
Textbook
Number of Pages
552 Pages

Dimensions

Item Length
10.3in
Item Height
1.4in
Item Width
7.3in
Item Weight
41.4 Oz

Additional Product Features

Lc Classification Number
Qa402.3.S5446 2006
Reviews
"The dozens of helpful step-by-step examples, visual illustrations, and lists of exercises proposed at the end of each chapter significantly facilitate a reader's understanding of the book's content." ("Computing Reviews.com," December 4, 2006), "This book is obviously written with care and reads very easily. A very valuable resource for students, teachers, and practitioners...highly recommended." ( CHOICE , February 2007) "The dozens of helpful step-by-step examples, visual illustrations, and lists of exercises proposed at the end of each chapter significantly facilitate a reader's understanding of the book's content." ( Computing Reviews.com , December 4, 2006)
Copyright Date
2006
Topic
System Theory, Electrical, Optimization
Lccn
2006-040065
Dewey Decimal
629.8/312
Intended Audience
Scholarly & Professional
Dewey Edition
22
Illustrated
Yes
Genre
Technology & Engineering, Science, Mathematics

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