Sizing mixed-mode circuits by multi-objective evolutionary algorithms

I. Guerra-Gómez, E. Tlelo-Cuautle, Trent McConaghy, L. G. de la Fraga, G. Gielen, G. Reyes-Salgado, J. Muñoz-Pacheco
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引用次数: 4

Abstract

We show the behavior of the generations of two multi-objective evolutionary algorithms (MOEAs) for the optimal sizing of two mixed-mode circuits. The non-sorting genetic algorithm (NSGA-II), and the MOEA based on decomposition (MOEA/D) are used to size a second generation current conveyor (CCII+) and a current-feedback operational amplifier (CFOA). Both MOEAs take into account design constraints, and link HSPICE to evaluate the electrical characteristics of the CCII+ and CFOA. Differential evolution is used as genetic operator to show the behavior of the generations of the two MOEAs.
我们展示了两种多目标进化算法(moea)的代行为,用于两个混合模式电路的最优尺寸。采用非排序遗传算法(NSGA-II)和基于分解的MOEA (MOEA/D)对第二代电流输送器(CCII+)和电流反馈运算放大器(CFOA)进行了尺寸确定。两个moea都考虑了设计约束,并链接HSPICE来评估CCII+和CFOA的电特性。采用差分进化作为遗传算子来表示两个moea的代行为。
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