LEADER 03739nam 22006255 450 001 9910847079503321 005 20250807150254.0 010 $a981-9980-63-1 024 7 $a10.1007/978-981-99-8063-5 035 $a(MiAaPQ)EBC31246282 035 $a(Au-PeEL)EBL31246282 035 $a(CKB)31320351800041 035 $a(DE-He213)978-981-99-8063-5 035 $a(EXLCZ)9931320351800041 100 $a20240401d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntroduction to Random Signals, Estimation Theory, and Kalman Filtering /$fby M. Sami Fadali 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (489 pages) 311 08$a981-9980-62-3 320 $aIncludes bibliographical references and index. 327 $aReview 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. 330 $aThis 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. 606 $aAutomatic control 606 $aRobotics 606 $aAutomation 606 $aAerospace engineering 606 $aAstronautics 606 $aTelecommunication 606 $aControl, Robotics, Automation 606 $aAerospace Technology and Astronautics 606 $aCommunications Engineering, Networks 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aAutomation. 615 0$aAerospace engineering. 615 0$aAstronautics. 615 0$aTelecommunication. 615 14$aControl, Robotics, Automation. 615 24$aAerospace Technology and Astronautics. 615 24$aCommunications Engineering, Networks. 676 $a519.544 700 $aFadali$b M. Sami$01724619 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910847079503321 996 $aIntroduction to Random Signals, Estimation Theory, and Kalman Filtering$94154632 997 $aUNINA