Kalman Filtering with Real-Time Applications
โ Scribed by Professor Charles K. Chui, Dr. Guanrong Chen (auth.)
- Publisher
- Springer Berlin Heidelberg
- Year
- 1987
- Tongue
- English
- Leaves
- 201
- Series
- Springer Series in Information Sciences 17
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Front Matter....Pages i-xv
Preliminaries....Pages 1-19
Kalman Filter: An Elementary Approach....Pages 20-32
Orthogonal Projection and Kalman Filter....Pages 33-49
Correlated System and Measurement Noise Processes....Pages 50-67
Colored Noise....Pages 68-77
Limiting Kalman Filter....Pages 78-98
Sequential and Square-Root Algorithms....Pages 99-110
Extended Kalman Filter and System Identification....Pages 111-124
Decoupling of Filtering Equations....Pages 125-136
Notes....Pages 137-151
Back Matter....Pages 153-191
โฆ Subjects
Optics, Optoelectronics, Plasmonics and Optical Devices;Mathematical Methods in Physics;Numerical and Computational Physics
๐ SIMILAR VOLUMES
<B>Kalman Filtering with Real-Time Applications</B> presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an ind
<p>Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirec
This book presents a thorough discussion of the mathematical theory of Kalman filtering. The filtering equations are derived in a series of elementary steps enabling the optimality of the process to be understood. It provides a comprehensive treatment of various major topics in Kalman-filtering theo
<p>Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirec