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Improved nonlinear observable degree analysis using data fusion

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Publication:2662522
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DOI10.1016/j.amc.2020.125613OpenAlexW3089989796MaRDI QIDQ2662522

Zhenyu Lu, Mengmeng Wang, Quanbo Ge, Shuaishuai Tang

Publication date: 14 April 2021

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2020.125613


zbMATH Keywords

nonlinear systemcondition numberCramer-Rao lower boundobservable degree


Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11)





Cites Work

  • An interval Kalman filtering with minimal conservatism
  • Bearings-only tracking of manoeuvring targets using particle filters
  • Sensitivity of an extended Kalman filter. I: Variation in the number of observers and types of observations
  • Asynchronous dissipative filtering for nonlinear jumping systems subject to fading channels
  • Attenuation of multiple in reflection seismic data using Kalman-Bucy filter
  • Conditional Posterior Cramér–Rao Lower Bounds for Nonlinear Sequential Bayesian Estimation
  • Cubature Kalman Filters




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