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首页> 外文期刊>Journal of Computational Electronics >On modeling of substrate loading in GaN HEMT using grey wolf algorithm
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On modeling of substrate loading in GaN HEMT using grey wolf algorithm

机译:用灰狼算法在GaN Hemt中底物装载的建模

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In this paper, four different equivalent circuit models to describe substrate loading effect in GaN HEMT on Si substrate are investigated. The effect is characterized by Z-parameter measurements of open de-embedding structure for 16×200-μm GaN HEMT on Si substrate. The grey wolf optimization (GWO)-based procedure is developed to extract optimal values for the model elements. The performance of the proposed technique is evaluated by using two other meta-heuristic optimizations, the well-known particle swarm and the recently developed whale algorithm. The three extraction procedures are evaluated in terms of their effectiveness and rate of convergences. The models are validated by means of S-parameters simulation for the considered device at different passive and active bias conditions. A very good agreement with measurements is achieved when using the GWO, validating its applicability for small- and large-signal modeling applications.
机译:本文研究了四种不同的等效电路模型,用于描述Si衬底上GaN HEMT中的底物负载效果。该效果的特征在于在Si衬底上进行16×200-μmGaN Hemt的开放式去嵌入结构的Z参数测量。基于灰狼优化(GWO)的过程是开发的,以提取模型元素的最佳值。通过使用其他另外的2个启发式优化,众所周知的粒子群和最近开发的鲸尔算法来评估所提出的技术的性能。三种提取程序在其有效性和收敛速率方面进行评估。通过不同被动和主动偏置条件的考虑设备的S参数仿真验证了模型。使用GWO时,实现了与测量值非常好的协议,验证其对小型和大信号建模应用的适用性。

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