Efficient computation with radial basis functions

该建议涉及开发更有效的计算技术，用于当数据结构少且可能处于高空间维时的信息重建。径向基函数（RBF）方法已被证明是该任务的一种流行选择。我们打算继续开发廉价的rbf预处理方法，并提供理论和数值实验，以支持数据各向异性时有效的重建计算方法。

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.