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Polyharmonic splines are used for function approximation and data interpolation. They are very useful for interpolation of scattered data in many dimensions. A special case are thin plate splines.〔R.L. Harder and R.N. Desmarais: (Interpolation using surface splines ). Journal of Aircraft, 1972, Issue 2, pp. 189-191〕〔J. Duchon: Splines minimizing rotation-invariant semi-norms in Sobolev spaces. Constructive Theory of Functions of Several Variables, W. Schempp and K. Zeller (eds), Springer, Berlin, pp.85-100〕 == Definition == where * is a real-valued vector of nx independent variables, * are N vectors of the same size as (often called centers) that the interpolated curve shall pass * are the N weights of the basis functions. * are the nx+1 weights of the polynomial. * The linear polynomial with the weighting factors improves the interpolation close to the "boundary" and especially the extrapolation "outside" of the centers . If this is not desired, this term can also be removed (see also figure below). The basis functions of polyharmonic splines are radial basis functions of the form: Other values of exponent k are not useful (such as ), because a solution of the interpolation problem might no longer exist. To avoid problems at r=0 (since ln(0) = -∞), the polyharmonic splines with the natural logarithm might be implemented as: The weights and are determined such that the function passes through given points (i=1,2,...,N) and fulfill the orthogonality conditions: To compute the weights, a symmetric, linear system of equations has to be solved: where Under very mild conditions (essentially, that at least nx+1 points are not in a subspace; e.g. for nx=2 that at least 3 points are not on a straight line), the system matrix of the linear system of equations is nonsingular and therefore a unique solution of the equation system exists. Once the weights are determined, interpolation requires to just evaluate the top most formula for the provided . Many practical details to implement and use polyharmonic splines are given in the book of Fasshauer.〔G.F. Fasshauer G.F.: (Meshfree Approximation Methods with MATLAB ). World Scientific Publishing Company, 2007, ISPN-10: 9812706348〕 In Iske〔 A. Iske: (Multiresolution Methods in Scattered Data Modelling ), Lecture Notes in Computational Science and Engineering, 2004, Vol. 37, ISBN 3-540-20479-2, Springer-Verlag, Heidelberg.〕 polyharmonic splines are treated as special cases of other multiresolution methods in scattered data modelling. 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Polyharmonic spline」の詳細全文を読む スポンサード リンク
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