Spline Approximation Using Knot Density Functions
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This paper, resulting from research collaboration with the UK National Physical Laboratory, is the first to present successfully a
simple method for controlling the location parameters in univariate spline approximations. Traditional highly non-linear
approaches are avoided by considering the parameters to be a function of a given density model. We present a number of
density models for a range of data types, such as dominant local variability. This paper delivers to a scientific discipline applying
polynomial spline approximations to recover discrete data to a high level of accuracy a method which avoids the need to
construct complicated mathematical models.
[1] Philip E. Gill,et al. Practical optimization , 1981 .
[2] M. Cox. The Least Squares Solution of Overdetermined Linear Equations Having Band or Augmented Band Structure , 1981 .
[3] M. Cox. The Numerical Evaluation of B-Splines , 1972 .
[4] Robert J. Boik,et al. Derivatives of the Incomplete Beta Function , 1998 .
[5] P M Harris,et al. Testing algorithms for free-knot spline approximation. , 2004 .