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首页> 外文期刊>IEEE Transactions on Circuits and Systems. 1 >Small-signal modeling for microwave FET linear circuits based on a genetic algorithm
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Small-signal modeling for microwave FET linear circuits based on a genetic algorithm

机译:基于遗传算法的微波FET线性电路小信号建模

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In this paper we present a new method to efficiently optimize small-signal equivalent circuits for microwave and millimeter-wave FET linear circuit design. The method couples the stochastic search of a Partially Elitistic Genetic Algorithm with a local search procedure. Up to 19 equivalent circuit elements have been included in the small-signal model for completeness and flexibility. Optimization examples are given for an ion-implanted MESFET up to 12 GHz, a pseudomorphic HEMT up to 50 GHz, and for synthetic data. The results show that the proposed algorithm is able to consistently provide an excellent fit between measured and calculated S-parameters without any need of a careful initial guess for the circuit element values. Also, once the device parasitics have been de-embedded, the algorithm is able to extract unique, physically meaningful values for the intrinsic device parameters, and it is numerically shown not to be affected by measurement uncertainties.
机译:在本文中,我们提出了一种新方法,可以有效地优化微波和毫米波FET线性电路设计中的小信号等效电路。该方法将局部精英遗传算法的随机搜索与局部搜索过程结合在一起。小信号模型中已包含多达19个等效电路元件,以实现完整性和灵活性。针对高达12 GHz的离子注入MESFET,高达50 GHz的假晶HEMT以及合成数据给出了优化示例。结果表明,所提出的算法能够始终如一地在测量和计算的S参数之间提供出色的拟合,而无需对电路元件值进行仔细的初始猜测。同样,一旦消除了设备寄生因素,该算法就能够为设备的固有参数提取唯一的,物理上有意义的值,并且通过数字显示不受测量不确定性的影响。

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