On the robustness of the Bayes and Wiener estimators under model uncertainty
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Publication:1679087
DOI10.1016/j.automatica.2017.06.005zbMath1373.93334arXiv1508.01904OpenAlexW2963847210MaRDI QIDQ1679087
Publication date: 8 November 2017
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1508.01904
minimax problemrobust filteringminimum entropy problemrisk-sensitive estimation problemTau divergence family
Filtering in stochastic control theory (93E11) Sensitivity (robustness) (93B35) Control/observation systems with incomplete information (93C41) Estimation and detection in stochastic control theory (93E10)
Related Items (5)
Robust fixed-lag smoothing under model perturbations ⋮ Adaptive risk-sensitive filter for Markovian jump linear systems ⋮ Robust distributed Kalman filtering with event-triggered communication ⋮ Convergence Analysis of a Family of Robust Kalman Filters Based on the Contraction Principle ⋮ On asymptotic properties of hyperparameter estimators for kernel-based regularization methods
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