A PSO Parameter Extraction Method for SOI MOSFETs based on BSIM SOI Model
首发时间:2012-01-05
Abstract:Abstract: A parameter extraction and optimization strategy using PSO (Particle Swarm Optimization) algorithm is presented for SOI (Silicon On Insulator) MOSFETs(Metal-Oxide -Semiconductor Field Effect Transistor) based on the BSIM SOI 3.1 model which is developed by the BSIM group of UC Berkeley. The global optimal strategy and standard PSO algorithm are implemented to fulfill the extraction of direct-current parameters, which are related to gate voltage and drain voltage. The values of the optimal parameters, which are got from multiple experiments, are as follows: inertia factor w=0; learning factor c1=c2=2; the initialization of the particle swarm is a random distribution; the value of swarm scale is 30. The algorithm shows a perfect convergence rate and can be used as a possible global extraction method for MOSFETs devices.
keywords: Microelectronics SOI MOSFETs Particle Swarm Optimization parameter extraction
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基于粒子群算法的BSIM SOI模型参数提取
摘要:本文提出了一种提取SOI (绝缘体上硅)器件参数的新方法,该方法基于粒子群优化算法,所使用的SOI模型由加州伯克利大学的BSIM课题组提出。本文主要利用粒子群算法对器件的直流参数进行了提取,这些直流参数的值依赖于栅压和漏压。经过大量的实验,得到了适用于BSIM SOI模型的最优参数:惯性因子w=0,学习因子c1=c2=2,粒子群的初始化采用随机分布,种群规模值取30。本算法显示出了非常好的收敛速度,本文的方法亦可以可以用作对其他种类的MOSFET(金属氧化物半导体场效应晶体管)进行全局参数提取。
关键词: 微电子学 SOI MOSFETs 粒子群算法 参数提取
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