The power distribution network (PDN) is an essential component in high speed circuits, and the impedance calculation of PDN becomes a hot topic. In this paper, we proposed a method to calculate the impedance of power ground grid (PGG), which is one type of the PDN, by using artificial neural network (ANN). First, the PGG is equivalent to a simple power ground plane (PGP). The equivalent PGP has the same dimension and port location but different relative permittivity and relative permeability of the substrate compared to the original PGG. Then, ANN is used to calculate the equivalent and of the equivalent PGP. Thus, the impedance of equivalent PGP can be obtained by using Green's function. The proposed method has been validated by numerical and measurement examples. The agreement and difference of the impedance results in both examples are also analyzed.

中文翻译：

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基于人工神经网络的电力地网阻抗计算

配电网络（PDN）是高速电路中必不可少的组成部分，PDN的阻抗计算成为热门话题。在本文中，我们提出了一种利用人工神经网络（ANN）计算电力接地网（PGG）阻抗的方法，该方法是PDN的一种。首先，PGG 相当于一个简单的电源地平面 (PGP)。与原始 PGG 相比，等效 PGP 具有相同的尺寸和端口位置，但基板的相对介电常数和相对磁导率不同。然后，ANN用于计算等价和等效的 PGP。因此，等效PGP的阻抗可以通过使用格林函数得到。所提出的方法已通过数值和测量示例进行了验证。还分析了两个例子中阻抗结果的一致性和差异性。