Smoothing for continuous dynamical state space models with sampled system coefficients based on sparse kernel learning
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DOI: 10.1007/s11071-020-05698-0
Abstract: A new smoother for a continuous dynamical state space model with sampled system coefficients is proposed. This is completely different from conventional approaches, such as Rauch–Tung–Striebel smoother. In the proposed method, the state vector as… read more here.
Keywords: state; state space; dynamical state; system coefficients ... See more keywords