Variance-Constrained Filtering for Stochastic Complex Systems
Theories and Algorithms
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Beschreibung
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.
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.
Combines existing and emerging concepts for incomplete information for variance-constrained filtering algorithms Introduces several efficient handling methods for the algorithm design Discusses boundedness and monotonicity of filtering algorithms and conditions to evaluate algorithm performance
Autor*in
Jun Hu
Themen in »Variance-Constrained Filtering for Stochastic Complex Systems«
Variance-constrained filtering Nonlinear time-varying dynamical systems Performance analysis Nonlinear systems Complex networks Stochastic nonlinearities Missing measurements Fading measurements Successive packet dropouts Sensor saturation Random sensor delays Randomly occurring quantization Randomly occurring deception attacks Event-triggered mechanism Random access protocol
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“This book is concerned with variance-constrained filtering problems and their applications for investigating some classes of time-varying dynamical systems with incomplete information. … This book is a research monograph whose intended audience is engineers, mathematicians, scientists, and graduate and postgraduate students in the fields of control engineering, signal processing, networked control systems, robotics, data analysis, and automation.” (Mykhailo Moklyachuk, Mathematical Reviews, March, 2026)
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