Filtering and System Identification: A Least Squares Approach Michel Verhaegen and Vincent Verdult are authors of an English-language textbook focused on filtering and system identification. This book covers the application of the least squares approach within linear state-space models and is suitable for students and researchers in engineering.
The book discusses reliable numerical methods for reconstructing missing information in complex systems. Readers gain insight into the use of filtering and system identification, starting with the Kalman filter and continuing through the estimation of complete models, noise statistics, and state estimators based on measurement data.
Essential background knowledge in linear matrix algebra and systems theory is provided, followed by a range of estimation and identification techniques within state-space models. With exercises and MATLAB simulations, it serves as a practical reference for graduate students and professionals in electrical engineering, mechanical engineering, and aerospace engineering.
This study book aligns with fields such as electronics engineering, communications engineering, and technology and engineering.