S. Nakamori (Japan), M.J. García-Ligero, A Hermoso, and J. Linares (Spain)
Estimation. Fixed-interval smoothing. Statisticalmodelling. Distributed parameter systems. Covarianceinformation.
This paper proposes a recursive least mean-squared error linear fixed-interval smoothing algorithm in distributed parameter systems. It is assumed that the state-space model of the signal to be estimated is unknown, and the algorithm only requires the second-order moments of the signal and the white noise perturbing its observations. Practical application of the proposed algorithm is illustrated with a restoration image problem.
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