Quadrature formulas (QFs) based on radial basis functions (RBFs) have become an essential tool for multivariate numerical integration of scattered data. Although numerous works have been published on RBF-QFs, their stability theory can still be considered as underdeveloped. Here, we strive to pave the way towards a more mature stability theory for global and function-independent RBF-QFs. In particular, we prove stability of these for compactly supported RBFs under certain conditions on the shape parameter and the data points. As an alternative to changing the shape parameter, we demonstrate how the least-squares approach can be used to construct stable RBF-QFs by allowing the number of data points used for numerical integration to be larger than the number of centers used to generate the RBF approximation space. Moreover, it is shown that asymptotic stability of many global RBF-QFs is independent of polynomial terms, which are often included in RBF approximations. While our findings provide some novel conditions for stability of global RBF-QFs, the present work also demonstrates that there are still many gaps to fill in future investigations.
翻译:基于辐射基函数的宽度公式(QFs)已成为分散数据多变数字集成的基本工具。尽管在RBF-QF上发表了许多著作,但稳定理论仍被视为欠发达。在这里,我们努力为全球和功能独立的RBF-QF建立一个更成熟的稳定理论。特别是,我们证明,在形状参数和数据点的某些条件下,这些基于简单支持的RFFs具有稳定性。作为改变形状参数的一种替代办法,我们通过允许用于数字集成的数据点数量大于用于生成RBF近似空间的中心数量,展示了如何利用最小方方法构建稳定的RBF-QFs。此外,我们发现,许多全球的RBF-QFs的无症状稳定性与多词无关,而这些词往往包含在RBFF的近似中。我们的调查结果为全球RBF-QFs的稳定提供了一些新的条件,但目前的工作也表明,今后的调查仍有许多差距。