In this article, we introduce a new variable shape parameter is called symmetric variable shape parameter (SVSP) for Gaussian radial basis functions (GRBFs). The GRBF has the shape parameter $c$, which plays an important role in the accuracy of the approximation. In this work, we will use it to? interpolate functions and solve linear boundary value problems (LBVP). Some numerical experiments are presented to show accuracy and robustness of the GRBF with SVSP strategy. These results have the best accuracy for the one- and two-dimensional interpolations and LBVP. Besides, the numerical results show that the SVSP for GRBF often outperforms constant shape parameter strategy.
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机译：在本文中，我们为高斯径向基函数（GRBF）引入了一个新的可变形状参数，称为对称可变形状参数（SVSP）。 GRBF具有形状参数$ c $，它在逼近精度中起着重要作用。在这项工作中，我们将使用它吗？插值函数并解决线性边值问题（LBVP）。提出了一些数值实验，以证明采用SVSP策略的GRBF的准确性和鲁棒性。这些结果对于一维和二维插值以及LBVP具有最佳精度。数值结果表明，用于GRBF的SVSP常常优于恒定形状参数策略。
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