03846nam a22005655i 4500 978-981-99-8063-5 DE-He213 20251030111801.0 cr nn 008mamaa 240401s2024 si | s |||| 0|eng d 9789819980635 978-981-99-8063-5 10.1007/978-981-99-8063-5 doi TJ212-225 TJ210.2-211.495 TJFM bicssc TEC007000 bisacsh TJFM thema Fadali, M. Sami. author. aut http://id.loc.gov/vocabulary/relators/aut 74599 Introduction to Random Signals, Estimation Theory, and Kalman Filtering [electronic resource] / by M. Sami Fadali. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XXI, 480 p. 118 illus., 79 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Review of Probability Theory -- Random Variables -- Random Signals (autocorrelation, power spectral density) -- Response of Linear Systems to Random Inputs (continuous, discrete) -- Estimation and Estimator Properties (small sample and large sample properties of estimators, CRLB) -- Least Square Estimation Likelihood (likelihood function, detection) -- Maximum Likelihood Estimation -- Minimum Mean-Square Error Estimation (Kalman Filter, information filter, filter stability) -- Generalizing the Basic Kalman Filter (colored noise, correlated noise, reduced-order estimator, Schmidt Kalman filter sequential computation) -- Prediction and Smoothing -- Nonlinear Filtering (Extended Kalman filter, unscented Kalman filter, ensemble Kalman filter, particle filter) -- The Expectation Maximization Algorithm -- Markov Models. This book provides first-year graduate engineering students and practicing engineers with a solid introduction to random signals and estimation. It includes a statistical background that is often omitted in other textbooks but is essential for a clear understanding of estimators and their properties. The book emphasizes applicability rather than mathematical theory. It includes many examples and exercises to demonstrate and learn the theory that makes extensive use of MATLAB and its toolboxes. Although there are several excellent books on random signals and Kalman filtering, this book fulfills the need for a book that is suitable for a single-semester course that covers both random signals and Kalman filters and is used for a two-semester course for students that need remedial background. For students interested in more advanced studies in the area, the book provides a bridge between typical undergraduate engineering education and more advanced graduate-level courses. Control engineering. Robotics. 59148 Automation. 59149 Aerospace engineering. 66335 Astronautics. 66336 Telecommunication. Control, Robotics, Automation. Aerospace Technology and Astronautics. 66339 Communications Engineering, Networks. SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819980628 Printed edition: 9789819980642 Printed edition: 9789819980659 https://doi.org/10.1007/978-981-99-8063-5 ZDB-2-INR ZDB-2-SXIT 58893 58893