Accurate derivative estimation from noisy data: a state-space approach

DOI10.1080/00207728908910103zbMath0663.93065OpenAlexW1972537776MaRDI QIDQ3815228

Sandro Fioretti, Leopoldo Jetto

Publication date: 1989

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207728908910103

zbMATH Keywords

optimal state estimationnoisy signalfixed-lag Kalman smootherNumerical differentiation of discrete observations

Mathematics Subject Classification ID

Related Items (5)

An iterative Kalman smoother/least-squares algorithm for the identification of delta-ARX models ⋮ Differential phase space reconstructed for chaotic time series ⋮ Realization and performance evaluation of a class of image models for recursive restoration problems ⋮ Identification of partial differential equation models for a class of multiscale spatio-temporal dynamical systems ⋮ Estimation of spatial derivatives and identification of continuous spatio-temporal dynamical systems

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• A regularization procedure for estimating cell kinetic parameters from flow-cytometry data
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• A direct approach to identify the noise covariances of Kalman filtering
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Estimation of a dispersion parameter in discrete Kalman filtering
• Numerical Differentiation and Regularization
• Adaptive filtering

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