Kalman Filtering Under Information Theoretic Criteria
Author | : Badong Chen |
Publisher | : Springer Nature |
Total Pages | : 304 |
Release | : 2023-09-19 |
ISBN-10 | : 9783031337642 |
ISBN-13 | : 3031337646 |
Rating | : 4/5 (646 Downloads) |
Download or read book Kalman Filtering Under Information Theoretic Criteria written by Badong Chen and published by Springer Nature. This book was released on 2023-09-19 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.