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Optimal recursive estimation of raw data
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DOI：10.1007/s10479-004-5039-5.png)
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We present a new approach to the optimal estimation of random vectors. The approach is based on a combination of a specific iterative procedure and the solution of a best approximation problem with a polynomial approximant. We show that the combination of these new techniques allow us to build a computationally effective and flexible estimator. The strict justification of the proposed technique is provided.
Keyword:
error minimization
stochastic vector
optimal estimate
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