THE UNSCENTED KALMAN FILTER, A POWERFUL TOOL FOR DATA ANALYSIS

DOI10.1142/S0218127404010515zbMath1129.93541MaRDI QIDQ4655678

Udo Schwarz, A. Sitz, Juergen Kurths

Publication date: 8 March 2005

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

zbMATH Keywords

chaosnonlinear systemsParameter estimationobservational noise

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45)

Related Items (3)

A METHOD FOR PARAMETER ESTIMATION IN LUR'E SYSTEMS ⋮ EXPERIMENTAL RESULTS ON CHUA'S CIRCUIT ROBUST SYNCHRONIZATION VIA LMIs ⋮ A combined method to estimate parameters of neuron from a heavily noise-corrupted time series of active potential

Cites Work

• New exact nonlinear filters with large Lie algebras
• A family of embedded Runge-Kutta formulae
• Tracking and data association
• Sequential Monte Carlo Methods in Practice
• A chaotic attractor from Chua's circuit
• The double scroll family
• Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems

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