LEADER 04483nam 22007935 450 001 9910739450403321 005 20240710090432.0 010 $a3-031-33764-6 024 7 $a10.1007/978-3-031-33764-2 035 $a(MiAaPQ)EBC30711947 035 $a(Au-PeEL)EBL30711947 035 $a(DE-He213)978-3-031-33764-2 035 $a(PPN)272273635 035 $a(CKB)28004897300041 035 $a(EXLCZ)9928004897300041 100 $a20230818d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aKalman Filtering Under Information Theoretic Criteria /$fby Badong Chen, Lujuan Dang, Nanning Zheng, Jose C. Principe 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (304 pages) 311 08$aPrint version: Chen, Badong Kalman Filtering under Information Theoretic Criteria Cham : Springer International Publishing AG,c2023 9783031337635 327 $aChapter 1. Introduction -- Chapter 2. Kalman filtering -- Chapter 3. Information theoretic criteria -- Chapter 4. Kalman Filtering Under Information Theoretic Criteria -- Chapter 5. Extended Kalman Filtering Under Information Theoretic Criteria -- Chapter 6. Unscented Kalman Filter Under Information Theoretic Criteria -- Chapter 7. Cubature Kalman Filtering Under Information Theoretic Criteria -- Chapter 8. Additional Topics in Kalman Filtering Under Information Theoretic Criteria. 330 $aThis book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering. Provides Kalman filters under information theoretic criteria to achieve excellent performance in a range of applications; Presents each chapter with a brief review of fundamentals and then focuses on the topic?s most important properties; Geared to students? understanding of linear algebra, signal processing, and statistics. 606 $aSignal processing 606 $aMathematical physics 606 $aEconometrics 606 $aEngineering mathematics 606 $aEngineering$xData processing 606 $aArtificial intelligence 606 $aSignal, Speech and Image Processing 606 $aMathematical Methods in Physics 606 $aTheoretical, Mathematical and Computational Physics 606 $aQuantitative Economics 606 $aMathematical and Computational Engineering Applications 606 $aArtificial Intelligence 606 $aFiltres digitals (Matemātica)$2thub 606 $aFiltre de Kalman$2thub 608 $aLlibres electrōnics$2thub 615 0$aSignal processing. 615 0$aMathematical physics. 615 0$aEconometrics. 615 0$aEngineering mathematics. 615 0$aEngineering$xData processing. 615 0$aArtificial intelligence. 615 14$aSignal, Speech and Image Processing . 615 24$aMathematical Methods in Physics. 615 24$aTheoretical, Mathematical and Computational Physics. 615 24$aQuantitative Economics. 615 24$aMathematical and Computational Engineering Applications. 615 24$aArtificial Intelligence. 615 7$aFiltres digitals (Matemātica) 615 7$aFiltre de Kalman 676 $a621.3815324 700 $aChen$b Badong$01424589 701 $aDang$b Lujuan$01424590 701 $aZheng$b Nanning$01424591 701 $aPrincipe$b Jose C$01424592 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910739450403321 996 $aKalman Filtering under Information Theoretic Criteria$93553892 997 $aUNINA