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Comparative analog circuit design automation based on multi-objective evolutionary algorithms: An application on CMOS opamp

机译:基于多目标进化算法的比较模拟电路设计自动化:CMOS Opamp的应用

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Automation of analog integrated circuit (IC) design process is very important because of the optimization contradictions. In this study, benefits of multi-objective evolutionary algorithms are presented on two stage operational amplifier design using Harmony Search Algorithm (HSA) and Non-dominated Sorting Genetic Algorithm (NSGA-II). HSA is a new kind of multi-objective evolutionary algorithm which was inspired from the musicians those are looking for the best combination of musical sounds of different instruments that produces most pleasing sound. NSGA-II is an advanced version of genetic algorithm. It combines both current parents and their child population to select new parents. These kinds of design automation tools are required for analog circuit design because there are several contradictions in the design. In this work, transistor sizes which effects all constraints indirectly were automatically synthesized by HSA an NSGA-II.
机译:由于优化矛盾,模拟集成电路(IC)设计过程的自动化非常重要。在这项研究中,使用和声搜索算法(HSA)和非主导的分类遗传算法(NSGA-II)的两个阶段运算放大器设计中提供了多目标进化算法的益处。 HSA是一种新的多目标进化算法,它受到了音乐家的启发,这些算法正在寻找产生最令人愉悦的声音的不同仪器的最佳音乐声音组合。 NSGA-II是遗传算法的先进版本。它结合了当前的父母和他们的孩子人口来选择新的父母。模拟电路设计需要这些设计自动化工具,因为设计中有几个矛盾。在这项工作中,晶体管尺寸由HSA A NSGA-II自动合成所有约束的影响。

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