D
Derui Ding
Researcher at University of Shanghai for Science and Technology
Publications - 186
Citations - 9503
Derui Ding is an academic researcher from University of Shanghai for Science and Technology. The author has contributed to research in topics: Computer science & Filter (signal processing). The author has an hindex of 39, co-authored 151 publications receiving 5756 citations. Previous affiliations of Derui Ding include Northeast Petroleum University & Swinburne University of Technology.
Papers
More filters
Journal ArticleDOI
Stability Analysis of Covariance Intersection-Based Kalman Consensus Filtering for Time-Varying Systems
TL;DR: A novel detectability condition, i.e., collectively uniform detectability, is proposed to ensure the error covariances of the CIKCF are uniformly bounded, and the estimation errors are proven to be exponentially bounded in mean square with the aid of the stochastic stability lemma.
Journal ArticleDOI
On Design of Robust Fault Detection Filter in Finite-Frequency Domain With Regional Pole Assignment
TL;DR: This brief is concerned with the fault detection filter design problem for an uncertain linear discrete-time system in the finite-frequency domain with regional pole assignment and an iterative algorithm for designing the desired FD filter is proposed by evaluating the threshold on the generated residual function.
Journal ArticleDOI
Finite-horizon bounded synchronisation and state estimation for discrete-time complex networks: local performance analysis
TL;DR: A new local description of the bounded H ∞ synchronisation performance index is proposed, which considers only the synchronisation errors among neighbours, and a more general sector-bounded condition is presented, where the parameter matrices are different for different node.
Journal ArticleDOI
Networked recursive filtering for time-delayed nonlinear stochastic systems with uniform quantisation under Round-Robin protocol
TL;DR: In this paper, the design of networked recursive filter is investigated for a kind of nonlinear stochastic systems subject to missing measurements, fixed time-delay and uniform quantisation under the Round-Robin protocol.
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Receding horizon filtering for a class of discrete time-varying nonlinear systems with multiple missing measurements
TL;DR: By exploiting the projection theory combined with stochastic analysis techniques, a Kalman-type receding horizon filter is put forward to facilitate the online applications and a novel estimation scheme of state covariance matrices is proposed to guarantee the implementation of the filtering algorithm.