Doubly Robust Smoothing of Dynamical Processes via Outlier Sparsity Constraints

DOI10.1109/TSP.2011.2161300zbMath1391.93281arXiv1104.5286MaRDI QIDQ4573213

Shahrokh Farahmand, Daniele Angelosante, Georgios B. Giannakis

Publication date: 18 July 2018

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1104.5286

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Nonparametric robustness (62G35) Estimation and detection in stochastic control theory (93E10) Data smoothing in stochastic control theory (93E14)

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Generalized System Identification with Stable Spline Kernels ⋮ Joint maximum \textit{a posteriori} state path and parameter estimation in stochastic differential equations ⋮ Generalized Kalman smoothing: modeling and algorithms ⋮ Robust fixed-lag smoothing under model perturbations ⋮ On sparsity‐inducing methods in system identification and state estimation ⋮ Estimation of ARMAX processes with noise corrupted output signal observations ⋮ Maximum a posteriori state path estimation: discretization limits and their interpretation ⋮ Moving horizon estimation for ARMAX processes with additive output noise ⋮ Maximum correntropy Kalman filter ⋮ An iterative algorithm for \(l_1\)-norm approximation in dynamic estimation problems

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