一般化インバース理論に基づく離散データの平滑化

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  • A Smooth Fitting Based on a Generalized Inverse Theory

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説明

A Generalized inverse theory is applied to a multivariate smooth fitting for irregularly spaced data. A smoothing function is expanded with cubic B-spline basis with equally spaced dense knots. Their coefficients are obtained by a least squares procedure using the a priori ioforrnation that the first and the second derivatives of the function are everywhere zero Plus random errors. The method is also regarded as an FEM approximation of a lateral deformation of an elastic bar or plate which is under tension and is pulled to data points by springs.

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