Escaping the native space of Sobolev kernels by interpolation
Abstract
Classical convergence analysis for kernel interpolation typically assumes that the target function f lies in the reproducing kernel Hilbert space Hk\!() induced by a kernel on a domain ⊂RN. For many applications, however, this assumption is overly restrictive. We develop a general framework for analyzing the convergence of kernel interpolation beyond the native space. Let A() and B() be Banach spaces with continuous embeddings Hk\!() A() B(), assume point evaluation is continuous on A(), and that Hk\!() is dense in A(). For a nested sequence of node sets (Xn)n1⊂ with n Xn dense, we characterize convergence of the kernel interpolants in the B()-norm for all target functions in A() via the uniform boundedness of the interpolation operators \,nA,B:A() B(). This yields a necessary and sufficient condition under which kernel interpolation extends beyond Hk\!(). Specializing to Sobolev kernels of order τ>N/2 on bounded Lipschitz domains, we show that every f ∈ C() can be approximated in the L2()-norm by interpolation using quasi-uniform nested centers. Moreover, for a subclass of Sobolev kernels (including integer-order Mat\'ern kernels), we prove that the Lebesgue constant is uniformly bounded on [a,b]⊂R under quasi-uniform centers; within our framework this implies supremum norm convergence of the interpolants for every target functions f ∈ C([a,b]).
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