In this paper, it is shown that an extension of the formulas used to calculate the parameters of the one-dimensional canonical piecewise-linear model leads to a generalized methodology which can be also applicable to two dimensions. The proposal is based on an approach by which a two-dimensional function is reconstructed by the collection of parallel projections of one-dimensional functions. In order to verify the performance of this proposal, numerical simulations are contrasted to those obtained from the standard high-level canonical piecewise-linear methodology. The comparison reveals that our proposal allows the construction of the function not only requiring a shorter run time but also demanding less memory.

本文表明，对用于计算一维规范分段线性模型参数的公式的扩展导致了一种通用方法，该方法也可应用于二维。该提议基于一种方法，通过该方法通过收集一维函数的平行投影来重建二维函数。为了验证该建议的性能，将数值模拟与从标准高级规范分段线性方法中获得的数值模拟进行对比。通过比较可以看出，我们的建议不仅允许构建功能，而且运行时间更短，而且所需的内存更少。