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— Two approaches, the extended Kalman filter (EKF) and moving horizon estimation (MHE), are discussed for state estimation for nonlinear dynamical systems under packet-dropping networks. For the EKF, we provide sufficient conditions that guarantee a bounded EKF error covariance. For MHE, a natural scheme on organizing the finite horizon window is proposed(More)
Random search trees have the property that their depth depends on the order in which they are built. They have to be balanced in order to obtain a more efficient storage-and-retrieval data structure. Balancing a search tree is time consuming. This explains the popularity of data structures which approximate a balanced tree but have lower amortized balancing(More)
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