$C^2$-continuous Hermite interpolation of streaming data with the use of cubic splinelets – building blocks for $C^2$-continuous cubic splines – is presented. Two specific types of splinelets, denoted as A and B, are formally defined (in closed form for equidistant internal knots) and then comparatively evaluated in a series of numerical experiments. The presented results show that the interpolant based on the cubic spline of type B outperforms not only its quintic correspondent, but also the ($C^1$-continuous only!) cubic Hermite spline. The proposed approach can be directly applied to streams that do or do not contain data related to the second derivative of the interpolated function, and to multidimensional curves/trajectories defined parametrically. One other possible application would be processing data sets that are too large to fit in memory.

$C^2$- 使用三次样条对流数据进行连续Hermite 插值- 用于构建块$C^2$- 连续三次样条 - 呈现。两种特定类型的样条，表示为A和B，被正式定义（等距内部结的封闭形式），然后在一系列数值实验中进行比较评估。所呈现的结果表明，基于B 型三次样条的插值不仅优于其五次对应，而且还优于 ($C^1$-仅连续！）三次 Hermite 样条。所提出的方法可以直接应用于包含或不包含与插值函数的二阶导数相关的数据的流，以及参数化定义的多维曲线/轨迹。另一种可能的应用是处理太大而无法放入内存的数据集。