Computer Aided Design of Microwave Circuits Based on BP Neural Networks

Junze Liu, Miao Yu
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Abstract

In addition to meeting basic electrical characteristics, the design of a microwave circuit must also consider the ease and accuracy of the circuit model, the time required for circuit design, the availability of tolerance analysis, and the ability to optimize output. Artificial Neural Network (ANN) technology has recently been introduced into microwave circuit CAD and optimization due to its nonlinear mapping function and high real-time computing capability. This technology has been shown to significantly improve the accuracy of modeling and compensate for errors in traditional microwave circuit design methods. In this study, we propose a BP neural network-based modeling method for microwave integrated circuits. This model can be used for computer-aided integrated microsystem simulation and analysis. The fitting error(RMSE) between the original simulation data and the test data is reduced from 0.868 to 0.274 before and after compensation, demonstrating the effectiveness of the proposed method. Experimental results show that the accuracy of the circuit model is improved after the optimization of the BP neural network.
基于BP神经网络的微波电路计算机辅助设计
除了满足基本的电气特性外,微波电路的设计还必须考虑电路模型的简易性和准确性、电路设计所需的时间、公差分析的可用性以及优化输出的能力。人工神经网络(ANN)技术以其非线性映射功能和高实时性被引入到微波电路的CAD和优化中。该技术已被证明可以显著提高建模精度,弥补传统微波电路设计方法的误差。在这项研究中,我们提出了一种基于BP神经网络的微波集成电路建模方法。该模型可用于计算机辅助集成微系统仿真与分析。补偿前后原始仿真数据与试验数据的拟合误差(RMSE)由0.868降至0.274,验证了所提方法的有效性。实验结果表明,经过BP神经网络优化后,电路模型的精度得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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