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SaPOSM: an optimization method applied to parameter extraction of MOSFET models

机译:SaPOSM:一种用于MOSFET模型参数提取的优化方法

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Points out that SaPOSM integrates an efficient deterministic optimization algorithm, called POSM, with the popular stochastic optimization paradigm simulated annealing (SA). It offers great promise for improving the optimization results significantly while using only a moderate amount of computing time. Tested on a suite of multi-minima optimization benchmark problems, SaPOSM's performance rivals a recently reported fast simulated diffusion method. SaPOSM was used to extract the parameters of state-of-the-art submicron (0.3- mu m channel length) MOSFET transistors, and very favorable results have been obtained. For a second difficult parameter extraction problem (18 parameters, five different channel lengths), simulation results indicate that SaPOSM achieves performance comparable to the SA method. Specifically, both SA and SaPOSM are able to minimize the modeling error to several orders of magnitude smaller than that obtained using POSM alone. At the same time, the computing time taken by SaPOSM is only a very small fraction of that taken by the SA method.
机译:指出SaPOSM将称为POSM的高效确定性优化算法与流行的随机优化范例模拟退火(SA)集成在一起。它为在仅使用少量计算时间的情况下显着改善优化结果提供了广阔前景。经过一系列多重最小化优化基准问题的测试,SaPOSM的性能可与最近报道的快速模拟扩散方法相媲美。 SaPOSM用于提取最新的亚微米(0.3微米沟道长度)MOSFET晶体管的参数,并获得了非常令人满意的结果。对于第二个困难的参数提取问题(18个参数,五个不同的信道长度),仿真结果表明SaPOSM可以实现与SA方法相当的性能。特别是,SA和SaPOSM都能够将建模误差最小化到比单独使用POSM获得的建模误差小几个数量级。同时,SaPOSM所花费的计算时间只是SA方法所花费的时间的很小一部分。

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