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Stellar population synthesis is an important method in the galaxy andstar-cluster studies. In the stellar population synthesis models, stellarspectral library is necessary for the integrated spectra of the stellarpopulation. Usually, the stellar spectral library is used to the transformationbetween the stellar atmospheric parameters and the stellar spectrum. Theempirical stellar spectral library has irreplaceable advantages than thetheoretical library. However, for the empirical spectral library, thedistribution of stars is irregularly in the stellar atmospheric parameterspace, this makes the traditional interpolator difficult to get the accurateresults. In this work, we will provide an improved radial basis functioninterpolator which is used to obtain the interpolated stellar spectra based onthe empirical stellar spectral library. For this interpolator, we use therelation between the standard variance {\sigma} in the Gaussian radial basisfunction and the density distribution of stars in the stellar atmosphericparameter space to give the prior constraint on this {\sigma}. Moreover, wealso consider the anisotropic radius basis function by the advantage of thelocal dispersion of stars in the stellar atmospheric parameter space.Furthermore, we use the empirical stellar spectral library MILES to test thisinterpolator. On the whole, the interpolator has a good performance except forthe edge of the low-temperature region. At last, we compare this interpolatorwith the work in Cheng et al. (2018), the interpolation result shows an obviousimprovement. Users can use this interpolator to get the interpolated spectrabased on the stellar spectral library quickly and easily.

An upgraded interpolator of the radial basis functions network for spectral calculation based on empirical stellar spectral library