基于遗传算法的GaN hemt分布式小信号模型提取方法

2010 IEEE International Conference on Semiconductor Electronics (ICSE2010) Pub Date : 2010-06-28 DOI:10.1109/SMELEC.2010.5549476

Anwar Jarnda

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引用次数: 9

摘要

本文提出并实现了一种基于遗传算法的GaN HEMT小信号模型参数提取方法。采用遗传算法优化，为分布式模型元素生成高质量可靠的起始值。然后使用局部优化技术对该值进行细化，以找到每个模型元素的最优值。通过模拟8x125µm栅极宽度GaN HEMT在宽偏置范围内的s参数测量，验证了所开发的提取方法。

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Genetic algorithm based extraction method for distributed small-signal model of GaN HEMTs

In this paper, an improved small-signal model parameter extraction method, using genetic algorithm (GA), is presented and implemented for GaN HEMT. The GA optimization is used to generate a high quality reliable starting values for the elements of distributed model. This value are then refined using local optimization technique to find optimal value for each model element. The developed extraction method is validated by simulating S-parameter measurements of a 8x125-µm gate width GaN HEMT over a wide bias range.

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来源期刊

2010 IEEE International Conference on Semiconductor Electronics (ICSE2010)

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