LEADER 04165nam 22006855 450 001 9910999684703321 005 20250430130231.0 010 $a981-9626-37-4 024 7 $a10.1007/978-981-96-2637-3 035 $a(CKB)38672170600041 035 $a(DE-He213)978-981-96-2637-3 035 $a(MiAaPQ)EBC32063912 035 $a(Au-PeEL)EBL32063912 035 $a(EXLCZ)9938672170600041 100 $a20250430d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aVariance-Constrained Filtering for Stochastic Complex Systems $eTheories and Algorithms /$fby Jun Hu, Zidong Wang, Chaoqing Jia 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (XV, 310 p. 127 illus., 121 illus. in color.) 225 1 $aIntelligent Control and Learning Systems,$x2662-5466 ;$v18 311 08$a981-9626-36-6 327 $aIntroduction -- Recursive Filtering and Boundedness Analysis with ROQ -- Resilient Filtering with Stochastic Uncertainties and Incomplete Measurements -- Event-Triggered Resilient Filtering with Stochastic Uncertainties and SPDs -- Event-triggered Filtering with Missing Measurements -- Fault Estimation Against Randomly Occurring Deception Attacks -- Fault Estimation with Packet Dropouts and ROUs -- Fault Estimation with Randomly Occurring Faults and Sensor Saturations -- State Estimation for Complex Networks with Missing Measurements -- Quantized State Estimation for Complex Networks with Uncertain Inner Coupling -- Event-Based State Estimation for Complex Networks under UOPs -- Event-Based State Estimation for Complex Networks with Fading Observations and UST -- State Estimation for Complex Networks with Uncertain Observations and Coupling Strength -- Conclusions and Future Work. 330 $aThis book is concerned with the variance-constrained optimized filtering problems and their potential applications for nonlinear time-varying dynamical systems. The distinguished features of this book are highlighted as follows. (1) A unified framework is provided for handling the variance-constrained filtering problems of nonlinear time-varying dynamical systems with incomplete information. (2) The application potentials of variance-constrained optimized filtering in networked time-varying dynamical systems are outlined. It contains some new concepts, new models and new methodologies with practical significance in control engineering and signal processing. It is a collection of several research results and thereby serves as a useful reference for upper undergraduate, postgraduate and engineers who are interested in studying (i) the variance-constrained filtering, (ii) recent advances affected by incomplete information and (iii) potential applications in practical engineering systems. 410 0$aIntelligent Control and Learning Systems,$x2662-5466 ;$v18 606 $aDynamics 606 $aDynamics 606 $aNonlinear theories 606 $aAutomatic control 606 $aSystem theory 606 $aControl theory 606 $aDynamical Systems 606 $aApplied Dynamical Systems 606 $aControl and Systems Theory 606 $aSystems Theory, Control 615 0$aDynamics. 615 0$aDynamics. 615 0$aNonlinear theories. 615 0$aAutomatic control. 615 0$aSystem theory. 615 0$aControl theory. 615 14$aDynamical Systems. 615 24$aApplied Dynamical Systems. 615 24$aControl and Systems Theory. 615 24$aSystems Theory, Control. 676 $a515.39 700 $aHu$b Jun$4aut$4http://id.loc.gov/vocabulary/relators/aut$0696065 702 $aWang$b Zidong$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aJia$b Chaoqing$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910999684703321 996 $aVariance-Constrained Filtering for Stochastic Complex Systems$94375894 997 $aUNINA