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• W2073232457 abstract "We propose a skew-radial basis function (sRBF) expansion for the empirical model fitting problem. sRBFs employ a standard radial term, which is now made asymmetric by modulating, or skewing it with another function. The additional parameters in the skewing function permit the composite radial basis function to more flexibly adapt its shape to the data. We present several examples that illustrate the utility of sRBF representations for both the overdetermined data fitting problem and the data interpolation problem. We derive conditions under which skew perturbations of positive definite interpolation matrices remain positive definite. We observe that the sRBFs are particularly effective for producing uniform approximations and fitting jump discontinuities. We present an application to the time-series prediction of the maximum wind intensity of a hurricane and outline future work in image processing. The resulting sRBF models have reduced order, improved accuracy, and interpolation matrices with lower condition numbers." @default.
• W2073232457 created "2016-06-24" @default.
• W2073232457 creator A5009102574 @default.
• W2073232457 creator A5061567476 @default.
• W2073232457 date "2010-01-01" @default.
• W2073232457 modified "2023-09-25" @default.
• W2073232457 title "Skew-Radial Basis Function Expansions for Empirical Modeling" @default.
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• W2073232457 doi "https://doi.org/10.1137/08072293x" @default.
• W2073232457 hasPublicationYear "2010" @default.
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