Abstract
It is well known that it is possible to enhance the approximation properties of a kernel operator by increasing its support size. There is an obvious tradeoff between higher approximation order of a kernel and the complexity of algorithms that employ it. A question is then asked: how do we compare the efficiency of kernels with comparable support size? We follow Blu and Unser and choose as a measure of the efficiency of the kernels the first leading constant in a certain error expansion. We use time domain methods to treat the case of globally supported kernels in L p (R d), 1≤p≤∞.
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Dekel, S., Leviatan, D. On Measuring the Efficiency of Kernel Operators in L p (R d). Advances in Computational Mathematics 20, 53–65 (2004). https://doi.org/10.1023/A:1025838129042
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DOI: https://doi.org/10.1023/A:1025838129042