"This book is the first systematic investigation and analysis of batch state estimators and recursive forms. It begins by introducing the reader to the state estimation approach, then discusses the properties of finite impulse response (FIR) state estimators and provides a brief historical overview. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, and deal with optimal FIR filtering and considers a posteriori and a priori optimal, optimal ...
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"This book is the first systematic investigation and analysis of batch state estimators and recursive forms. It begins by introducing the reader to the state estimation approach, then discusses the properties of finite impulse response (FIR) state estimators and provides a brief historical overview. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, and deal with optimal FIR filtering and considers a posteriori and a priori optimal, optimal unbiased, and limited memory batch and recursive algorithms. Other topics covered include solving the q-lag FIR smoothing problem, introducing the receding horizon (RH) FIR state estimation approach, and developing the theory of FIR state estimation under disturbances. The book closes by discussing the theory of FIR state estimation for uncertain systems and providing several applications where the FIR state estimators are used effectively."--
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