Efficient computation with radial basis functions

该建议是关于发展更有效的计算技术，为重建的信息时，数据具有很小的结构，可能是在高的空间维。径向基函数（RBF）方法已被证明是一个流行的选择，这项任务。我们打算继续发展廉价的预处理方法RBFs和提供理论和数值实验，以支持有效的计算方法重建时，数据是各向异性的。

The proposal is concerned with developing more effective computational techniques for the reconstruction of information when the data has little structure and may be in high space dimension.Radial basis function (RBF) methods have proved a popular choice for this task. We intend to continue the development of cheap preconditioning methods for RBFs and provide theory and numerical experiments to support efficient computational methods for reconstruction when data is anisotropic.