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提出了一种新的基于布谷鸟搜索算法的片上电感模型参数优化算法。布谷鸟搜索算法对复杂非线性非凸函数的优化效果显著,这种函数的特点与半导体器件紧凑型模型参数和优化目标之间的非线性特性相近。该算法开发了模型参数交叉操作,将两个解空间的对应参数交换位置,避免敏感度高的参数对敏感度低的参数的过度影响。引入了自适应参数,使算法的搜索步长能自适应调整,既不会因为步长太大跳过最优解,也不会因为步长太小导致收敛速度慢。采用集成电路工艺片上螺旋电感的实测数据对该算法进行验证,得到较好的拟合度。提出的模型优化算法可适用于集成电路器件模型的自动优化。
A new parameter optimization algorithm for on-chip inductor model based on Cuckoo search algorithm is proposed. Cuckoo search algorithm has significant effect on the optimization of complex nonlinear non-convex functions. The characteristics of this function are similar to those of the compact model of semiconductor devices and the optimization target. The algorithm develops the cross-operation of model parameters and exchanges the corresponding parameters of the two solution spaces to avoid the excessive influence of the sensitive parameters on the less sensitive parameters. The adaptive parameter is introduced to make the searching step of the algorithm adaptively adjusted. The optimal solution can not be skipped because the step size is too large, and the convergence speed is not slow because the step size is too small. The algorithm is verified by the measured data of the on-chip spiral inductor of the integrated circuit, and a better fitting degree is obtained. The proposed model optimization algorithm is suitable for the automatic optimization of integrated circuit device models.