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- W2071434102 abstract "Given an observation vector <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>y = Ax + nu</tex> , estimate the parameter vector <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>x</tex> subject to the known constraint relationship <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>Kx = 0</tex> . The covariance matrix <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>R</tex> of the measurement error <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>nu</tex> and <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>A</tex> are known block diagonal matrices. The best linear unbiased estimate of <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>x</tex> and its covariance is obtained and compared with a sequential suboptimal estimate." @default.
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- W2071434102 date "1972-03-01" @default.
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- W2071434102 title "Optimal smoothing of piecewise continuous functions (Corresp.)" @default.
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- W2071434102 doi "https://doi.org/10.1109/tit.1972.1054795" @default.
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