Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches Hardcover – Jun 23 2006
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"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)
From the Back Cover
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 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. 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.See all Product Description
Most Helpful Customer Reviews on Amazon.com (beta)
I would also recommend Gelb's book ` Applied Optimal Estimation `.
The book is true to the title and focuses on Kalman filter from several different perspectives (properties, implementation, modifications, etc.)
I am still reading the book, so far I have read ch.3, 5 and 15. I have found a very good comparison of Kalman filter derivation through RLSE route, and Bayesian way. A good comparison of both approaches.
Author is also good in consistently providing the references through out the book, if you choose you can take a deeper dive along the references to sort out details that may be relevant to implementation and research.
I must have to say, a prior applied background is necessary to really appreciate the contents of the book intuitively.
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