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Dwarfs your fear towards complicated mathematical derivations and proofs. Experience Kalman filter with hands-on examples to grasp the essence. A book long awaited by anyone who could not dare to put their first step into Kalman filter. The author presents Kalman filter and other useful filters without complicated mathematical derivation and proof but with hands-on examples in MATLAB that will guide you step-by-step. The book starts with recursive filter and basics of Kalman filter, and gradually expands to application for nonlinear systems through extended and unscented Kalman filters. Also, some topics on frequency analysis including complem

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Book ID Asin: 1463648359
Book Title: Kalman Filter for Beginners: with MATLAB Examples
Book Author: Phil KimLynn Huh
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Book Price: unknown
Book Category: Books, Science & Math, Mathematics and unknown
Book Rating: 71 ratings

Kalman Filter for Beginners: with MATLAB Examples by Phil KimLynn Huh Book Review

Name: Arun Kumar​
Rating: 2.0 out of 5 stars
Title: VerylowvalueformoneyThecontentsareverybasicsurfacescratchofKalmanfilters
Date: Reviewed in the United States on January 31, 2022
Review: This book is not worth $70. The whole book is less than an introduction to Kalman filters. The author tried to make things very simple for a layman to understand, and hence did not go into any details of kalman filters. But then the book should have been priced appropriately. $70 for this joke? I wouldn't pay anything more than $20 for this one. You can get better value for money by watching the entire free lecture series by "Michel van Biezen" on Youtube. It teaches the ins and outs of Kalman filters from scratch like a university style lecture. The whole series has 42+ lectures on kalman filters alone. Do not buy this one.

Name: Jordan McBain
Rating: 5.0 out of 5 stars
Title: Amazing
Date: Reviewed in the United States on January 13, 2013
Review: This is an amazing book to start learning the Kalman Filter. I have been floundering around trying to find a good resource to gain a good practical understanding of the subject; while Zarchan's book is quite good, I believe that this book should form the basis of any beginning effort in understand or applying the Kalman Filter. The book's explanations and examples will put the reader in a position to make use of this technology in very short order.Comments from other reviewers about the book's "KorEnglish" are largely without merit. There are some very minor translations problems that almost always arise when the author/interpreter try to use "cute" expressions. These expressions are almost always used to soften the blow of learning the theory and I can do nothing but applaud them for their efforts in this respect. There are no translation problems that will inhibit the reader from absorbing this book's contents.In my view of the state of Kalman filter textbooks, there remains a need for a resource that pedagogically explains the underlying mathematics of the Kalman filter (which this book largely omits in order to keep a focus on practical application).The books by Kim and Zarchan constitute a good starting place for this complicated subject matter. I heartily recommend this book.

Name: Dan H.
Rating: 5.0 out of 5 stars
Title: AnexcellentintroductiontoKalmanFilters
Date: Reviewed in the United States on November 5, 2021
Review: I've tried getting started with Kalman Filters on a number of occasions but found it difficult to understand the purpose of the many variables in the filter and how they interact. There are a lot of moving parts to a Kalman Filter. This book does an excellent job of taking things from the basics and guiding the reader through the steps and explaining the purpose of each part. The text was originally written in Korean, I believe, and the translation isn't perfect but is plenty good to get across the points in this highly technical subject.

Name: real san diego reader
Rating: 4.0 out of 5 stars
Title: StartHere
Date: Reviewed in the United States on May 4, 2015
Review: This book is a great introductory book for those who are new to Kalman Filtering. I don't know about other people, but I learn best when I'm given a gentle introduction before really getting my hands dirty. Unfortunately, most other resources for Kalman Filtering jump straight into the mathematical derivations before giving even a glimpse of its application. Furthermore, the existing MATLAB tutorials for Kalman Filters are overly complex for someone who's just trying to learn the basics. Therefore, my advice is to start with this book to get a "20,000 ft. view" before diving into a more thorough text (like the Zarchan and Musoff book). The translation is excellent, and the prose is clear and straight-forward. Obviously, it's a book intended for MATLAB users, but I believe it can be useful to non-MATLAB users as well.My only complaint about the book is that it's fairly expensive for what it is. That's the only reason I'm giving it 4 stars rather than 5.

Name: James V. Eccles
Rating: 4.0 out of 5 stars
Title: GoodGuideforthisScientist
Date: Reviewed in the United States on October 31, 2017
Review: The book was easy to follow, which is why I purchased the book. Other more technical presentations of the Kalman Filter are overly complex in order to be mathematically rigorous. This is a guide, and a good guide. I understood the Kalman Filter pretty well once I had created my own FORTRAN programs of each chapter. The one thing missing was a chapter on the ensemble Kalman Filter. Maybe in a future edition. I was able to take the next step into ensemble Kalman Filtering with ease because of the foundation obtained from this book.Certainly the familiar voice of the writing was a bit annoying, but that is not the point of this book. Learning the Kalman Filter is.

Name: Abraman
Rating: 5.0 out of 5 stars
Title: VeryGoodKalmanBookforSoftwareDeveloper
Date: Reviewed in the United States on June 5, 2013
Review: I have few books on Kalman filter. Most are mathematically rigorous which can make me lose the motivation to continue study the subject. Kalman filter books usually require me to understand few math disciplines such as probability, matrix, dynamic system before I can fully understand the derivation. But for this book you don't really have to be involved in the derivation process before you can take full advantage of KF. As a programmer I really appreciate this approach. Phil Kim explains each equation in the KF, and how to use it using MATLAB (which can be adapted to other language such as C++, C etc). He also stresses the importance of formulating good mathematical model on the problems as requisite to successful application of KF. Other books by Zarchan and Eli Brookner are also good books, but they are thicker and more rigorous, as such this book can complement them. Should be on the bookshelf of every engineer that designs and writes control software, and professional who manipulate huge amount of measured data.