Bayesian Real-Time System Identification

Discover the cutting-edge advancements in Bayesian Real-Time System Identification by Ke Huang, published in 2023 by Springer Verlag. This insightful book spans 276 pages and delves into a centralized Bayesian identification framework designed to tackle the complexities of real-time parameter estimation. Readers will explore essential topics such as outlier detection and the tracking of system and noise parameters. Whether you're a researcher or a practitioner in the field, this book offers valuable insights and methodologies that can enhance your understanding of Bayesian techniques in system identification. Don't miss the opportunity to elevate your expertise with this essential resource!