Welcome to the order page for a comprehensive guide to Kalman Filtering! The e-book is an essential resource for anyone looking to understand and implement Kalman Filters for various applications.
By ordering this book, you will gain access to:
The explanations are presented in a straightforward and intuitive manner, accompanied by examples and illustrations. Additionally, each section provides the necessary mathematical background to reinforce your comprehension.
This book is suitable for beginners and experts alike, focusing on practical applications and real-world scenarios. Whether you're a researcher, engineer, or student, you'll find valuable insights and actionable advice in this book.
The book includes 14 fully solved numerical examples to enhance your understanding of the concepts. Additionally, you can purchase the source code for all examples in either Python or MATLAB. The source code is designed with a modular structure and can be used as a starting point for implementing Kalman Filters, Extended Kalman Filters, and Unscented Kalman Filters for other systems beyond those covered in the book.
Please note that both the e-book and source code purchases are non-refundable.
The book is sold by 2Checkout (Verifone), a trusted global reseller. With a strong reputation for secure transactions and reliable service, 2Checkout ensures a seamless buying experience.
The book is being introduced at a promotional price for a limited time.
I want to thank you very much for the excellent presentation you put together on the Kalman filter. I have been trying for many years (>20...) to understand and apply a Kalman filter in my work, but I have never been close to understanding how to even start.
I have a number of "classic", brutal, books full of Kalman filter theory, collecting dust on my book shelf; I suspect the theory is all there, examples?.... who needs examples?....
Your presentation, with the many examples, starting with the estimation of a constant (the weight of the gold bars) and going up to the multi-dimensional system with an input, made, for me, all the difference in understanding.
Thank you very much.
Daniel Fischer, B.A.Sc., M.A.Sc, Ph.D.
Senior Electrical Engineer
Entrust Solutions Group
Kestrel Power Engineering
Dear Alex Becker,
as I have gained so much value out of your tutorial on many occasions – again, thank you very much! - I certainly have just bought your book (as well as the code).
As Kalman filtering is of increasing importance to many of the courses at my university I have asked our library to attach the book to our library holdings.
Mit freundlichen Grüßen
Prof. Dr. Gunther Schaaf
Fakultät Mobilität und Technik
Hochschule Esslingen – University of Applied Sciences
I just would like to appreciate you work.
I've been working with KF for 20 years and I think you approach is the best to clarify it.
We've just purchased the book to the University library (Maritime University of Szczecin, Poland).
And I plan to use it a bit in my lectures to students about KF in geodata fusion.
Ph.D. Eng. Witold Kazimierski
Faculty of Navigation
Maritime University of Szczecin