Abstract
Given a linear stochastic system of dimension n in either discrete or continuous time, the smoothing problem amounts to determining the least-squares estimates
for some finite interval [t 0, t 1]. When t 0 → −∞ and t 1 → ∞, we end up in the stationary setting of Sect. 14.3, and we shall use this fact to reduce the dimension of the smoothing algorithms.
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Lindquist, A., Picci, G. (2015). Smoothing and Interpolation. In: Linear Stochastic Systems. Series in Contemporary Mathematics, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45750-4_15
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