| 書目名稱 | Kalman Filtering Under Information Theoretic Criteria |
| 編輯 | Badong Chen,Lujuan Dang,Jose C. Principe |
| 視頻video | http://file.papertrans.cn/542/541748/541748.mp4 |
| 概述 | Provides Kalman filters under information theoretic criteria to achieve excellent performance in a range of applications.Presents each chapter with a brief review of fundamentals and then focuses on t |
| 圖書封面 |  |
| 描述 | 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.. |
| 出版日期 | Book 2023 |
| 關鍵詞 | Kalman filtering; state estimation; robust Kalman filtering; extended Kalman filtering; unscented Kalman |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-33764-2 |
| isbn_softcover | 978-3-031-33766-6 |
| isbn_ebook | 978-3-031-33764-2 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機版|小黑屋|
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