Interpolation capability of the periodic radial basis function

Author

Abe, Yoshinori ; Iiguni, Youji

Author_Institution

Div. of Syst. Sci. & Appl. Informatics, Osaka Univ., Toyonaka

fYear

0

fDate

0-0 0

Firstpage

1307

Lastpage

1310

Abstract

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

Keywords

fast Fourier transforms; frequency response; interpolation; radial basis function networks; FFT; fast Fourier transform; frequency response; interpolation; periodic RBF network; radial basis function network; regularization approach; Computer networks; Fast Fourier transforms; Frequency response; Function approximation; Image sampling; Informatics; Interpolation; Radial basis function networks; Spline; Technological innovation; frequency analysis; periodic radial basis function; periodic regularization; sampling theorem;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 2005 Fifth International Conference on

Conference_Location

Bangkok

Print_ISBN

0-7803-9283-3

Type

conf

DOI

10.1109/ICICS.2005.1689267

Filename

1689267