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Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches Hardcover – Jun 23 2006

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Product Details

  • Hardcover: 552 pages
  • Publisher: Wiley-Interscience; 1 edition (June 23 2006)
  • Language: English
  • ISBN-10: 0471708585
  • ISBN-13: 978-0471708582
  • Product Dimensions: 18.5 x 3.6 x 26.2 cm
  • Shipping Weight: 1.1 Kg
  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: #654,140 in Books (See Top 100 in Books)
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Product Description


"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, 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.

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Most Helpful Customer Reviews on (beta) 4.2 out of 5 stars 25 reviews
3 of 3 people found the following review helpful
4.0 out of 5 stars Good over all book with plenty of proofs March 9 2009
By P. Abeles - Published on
Format: Hardcover Verified Purchase
Overall I found the book to be very well written with plenty of proofs, which I really like. In the sections that I looked at (with one exception) I did not find any errors. For the more recent material, towards the end, I would highly recommend looking at the original papers in addition to what's in the book. Out of necessity some things are glossed over. In the case of the unscented Kalman filter the algorithm presented in the book has some issues. It is not exactly the same algorithm as in the original papers and will in fact produce a covariance matrix which is incorrect. However, on the whole I would highly recommend the book, especially for self learners.
5 of 5 people found the following review helpful
5.0 out of 5 stars Excellent for a newcomer Feb. 4 2009
By T. Driver - Published on
Format: Hardcover Verified Purchase
This book relates control theory elegantly, to those with a scientific background, but not much control theory history. Dan uses well laid out algorithmic approaches, suitable for programming, and examples to explain the details and show the complexities in action. I especially like the non-linear filtering chapters, and the comparison s between the Kalman Filter and other approaches (Particle Filter, etc.) I have several estimation/control theory texts, and this is the one I carry around with me.
1 of 1 people found the following review helpful
4.0 out of 5 stars Good introductory book, easy to understand Nov. 12 2008
By PC - Published on
Format: Hardcover Verified Purchase
Good introductory book on the subject. It is very easy to understand and does not require much background from the reader. For the more technically advanced readers, the pace may be a bit too slow. But nevertheless, I think it's a good introductory/self-study book especially for engineers.

I would also recommend Gelb's book ` Applied Optimal Estimation `.
1 of 2 people found the following review helpful
5.0 out of 5 stars A very good book, written well for independent study March 29 2013
By Waseem - Published on
Format: Hardcover Verified Purchase
I am a researcher and my background is in estimation, prediction modeling, and inferential models/methods. I found this book easy to follow (partly because of my background) in writing style.
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.
1 of 2 people found the following review helpful
5.0 out of 5 stars Very well written. Aug. 28 2008
By Amazon Customer - Published on
Format: Hardcover Verified Purchase
this book is very well written, easy to follow, with a lot of topics, and the derivations are shown thoroghly and in detail. One of the best estimation books I used. This book is recommended for both beginners andadvanced in estimation theory.