基于先验知识输入神经网络的微波功率放大器建模

J. Dooley, B. O'Brien, T. Brazil
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引用次数: 4

摘要

本文利用先验知识技术,提出了一种基于神经网络的微波功率放大器行为水平模型。模型参数提取和验证采用独立的宽带数字调制信号在时域。在相同的数据集上对准无记忆模型和无先验知识输入的神经网络模型进行了提取和测试。使用拟合优度统计的各种方法的比较表明,与没有先验知识输入的模型相比,本文提出的新模型表现更好,并且具有改进的泛化能力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prior Knowledge Input Neural Network for Microwave Power Amplifier Modeling
In this paper we present a novel neural network based behavioral level model for a microwave power amplifier (PA) utilizing a prior knowledge technique. Model parameters are extracted and verified using independent wideband digitally modulated signals in the time domain. Both quasi-memoryless and neural network models without any prior knowledge inputs are also extracted and tested with the same sets of data. Comparison of the various methods using goodness of fit statistics, show the new model presented here performs better and has improved generalization capabilities compared to models without prior knowledge inputs
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