Interpolation capability of the periodic radial basis function

A periodic radial basis function (RBF) network is proposed based on the regularization approach. The periodic RBF network can interpolate discrete data more efficiently than the conventional one since the coefficients of the network can be computed by using the fast Fourier transform (FFT). For the...

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Bibliographic Details
Published in2005 5th International Conference on Information Communications and Signal Processing pp. 1307 - 1310
Main Authors Abe, Y., Iiguni, Y.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 22.09.2006
Subjects
Computer networks
Fast Fourier transforms
frequency analysis
Frequency response
Function approximation
Image sampling
Informatics
Interpolation
periodic radial basis function
periodic regularization
Radial basis function networks
sampling theorem
Spline
Technological innovation
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ISBN9780780392830
0780392833
DOI10.1109/ICICS.2005.1689267

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Summary:A periodic radial basis function (RBF) network is proposed based on the regularization approach. The periodic RBF network can interpolate discrete data more efficiently than the conventional one since the coefficients of the network can be computed by using the fast Fourier transform (FFT). For the evaluation of the interpolation capability, the frequency response of the periodic RBF network is analyzed. It is then shown that the frequency response is asymptotically equivalent to the ideal sine interpolation, and that the periodic RBF network is closer to the ideal sine interpolation than the cubic spline and Lanczos interpolations
ISBN:9780780392830
0780392833
DOI:10.1109/ICICS.2005.1689267