04165nam 22006855 450 991099968470332120250430130231.0981-9626-37-410.1007/978-981-96-2637-3(CKB)38672170600041(DE-He213)978-981-96-2637-3(MiAaPQ)EBC32063912(Au-PeEL)EBL32063912(EXLCZ)993867217060004120250430d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierVariance-Constrained Filtering for Stochastic Complex Systems Theories and Algorithms /by Jun Hu, Zidong Wang, Chaoqing Jia1st ed. 2025.Singapore :Springer Nature Singapore :Imprint: Springer,2025.1 online resource (XV, 310 p. 127 illus., 121 illus. in color.) Intelligent Control and Learning Systems,2662-5466 ;18981-9626-36-6 Introduction -- 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.This 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.Intelligent Control and Learning Systems,2662-5466 ;18DynamicsDynamicsNonlinear theoriesAutomatic controlSystem theoryControl theoryDynamical SystemsApplied Dynamical SystemsControl and Systems TheorySystems Theory, ControlDynamics.Dynamics.Nonlinear theories.Automatic control.System theory.Control theory.Dynamical Systems.Applied Dynamical Systems.Control and Systems Theory.Systems Theory, Control.515.39Hu Junauthttp://id.loc.gov/vocabulary/relators/aut696065Wang Zidongauthttp://id.loc.gov/vocabulary/relators/autJia Chaoqingauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910999684703321Variance-Constrained Filtering for Stochastic Complex Systems4375894UNINA