Robust fusion filtering for multisensor time-varying uncertain systems: the finite horizon case

DOI10.1155/2016/2720549zbMath1417.94015OpenAlexW2302918896WikidataQ59123421 ScholiaQ59123421MaRDI QIDQ1723624

Xiaoliang Feng, Chenglin Wen, Funa Zhou

Publication date: 19 February 2019

Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/2720549

Mathematics Subject Classification ID

(H^infty)-control (93B36) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Cites Work

• Distributed \(H_\infty\)-consensus filtering in sensor networks with multiple missing measurements: the finite-horizon case
• Unified finite horizon \(H_{\infty}\) fusion filtering for networked dynamical system
• The optimal robust finite-horizon Kalman filtering for multiple sensors with different stochastic failure rates
• Distributed asynchronous fusion algorithm for sensor networks with packet losses
• Decentralized robust Kalman filtering for uncertain stochastic systems over heterogeneous sensor networks
• Sensors' optimal dimensionality compression matrix in estimation fusion
• H/sub /spl infin// filtering for multiple-time-delay measurements
• Linear estimation in Krein spaces. I. Theory
• Linear estimation in Krein spaces. II. Applications

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