Abstract
The efficient handling of matrices arising in surface interpolation and approximation with radial basis functions (RBF) is considered. To find a data-sparse approximation of the system matrix, the adaptive cross-approximation (ACA) technique is used. The approximation of the matrix requires O (Nlog2 N ) units of storage and arithmetic operations, where N is the number of interpolation points. Because basis functions are not explicitly used, the implementation is applicable to a wide class of interpolation kernels. Numerical examples involving generated data and measurements of formed sheet-metal parts are presented.
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