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首页> 外文期刊>International journal of RF and microwave computer-aided engineering >Fuzzy Neural-based Approaches For Efficient Rf/microwave Transistor Modeling
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Fuzzy Neural-based Approaches For Efficient Rf/microwave Transistor Modeling

机译：基于模糊神经的射频/微波晶体管建模方法

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摘要

In today's RF and microwave circuits, there is an ever-increasing demand for higher level of system integration that leads to massive computational tasks during simulation, optimization, and statistical analyses, requiring efficient modeling methods so that the whole process can be achieved reliably. Since active devices such as transistors are the core of modern RF/microwave systems, the way they are modeled in terms of accuracy and flexibility will critically influence the system design, and thus, the overall system performance. In this article, the authors present neural- and fuzzy neural-based computer-aided design techniques that can efficiently characterize and model RF/microwave transistors such as field-effect transistors and heterojunction bipolar transistors. The proposed techniques based on multilayer perceptrons neural networks and c-means clustering algorithms are demonstrated through examples.
机译：在当今的射频和微波电路中，对更高级别的系统集成的需求不断增长，导致在仿真，优化和统计分析过程中产生大量计算任务，需要高效的建模方法，以便可以可靠地实现整个过程。由于有源器件（例如晶体管）是现代RF /微波系统的核心，因此在准确性和灵活性方面对它们进行建模的方式将严重影响系统设计，进而影响整个系统的性能。在本文中，作者介绍了基于神经和模糊神经的计算机辅助设计技术，这些技术可以有效地表征和建模RF /微波晶体管，例如场效应晶体管和异质结双极晶体管。通过实例演示了基于多层感知器神经网络和c均值聚类算法的技术。

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