Vector fitting (VF) is a robust macromodeling method to construct rational models of a network based on tabulated frequency responses. When fitting a network with a large number of ports, the matrix equation in VF quickly grows into a formidable size. The conventional strategy is to break the equation into several small QR factorizations and then combine the results into a least-squares (LS) problem. In this letter, an alternative solution procedure is proposed, the complexity of which is 2.7 times smaller than the conventional approach in terms of floating-point operations (FLOPs). Test cases of 40–200-port data show that the actual computing time can be reduced by as much as 85%, which presents a considerable saving for large-scale problems.

中文翻译：

---

多端口大规模宏建模矢量拟合的加速

矢量拟合 (VF) 是一种稳健的宏建模方法，可基于列表频率响应构建合理的网络模型。当拟合具有大量端口的网络时，VF 中的矩阵方程很快就会变得非常庞大。传统的策略是将方程分解为几个小的 QR 分解，然后将结果组合成一个最小二乘 (LS) 问题。在这封信中，提出了一种替代解决方案，其复杂性比传统方法在浮点运算 (FLOP) 方面小 2.7 倍。40-200端口数据的测试用例表明，实际计算时间最多可以减少85%，这对于大规模问题来说是相当可观的。