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Simulated annealing Vs. Genetic Simulated Annealing for automatic transistor sizing

机译:模拟退火与 自动晶体管施胶遗传模拟退火

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Transistor size optimization is an important aspect of circuit design. Small and non-complex circuits can be designed easily using manual calculations and circuit simulations. But, as the complexity of circuits increases, manual design becomes too difficult and time consuming. Therefore, tools and techniques for automatic transistor sizing are of great importance in the area of circuit design. The goal of this paper is to implement Genetic Simulated Annealing algorithm as a tool for transistor sizing, and compare its performance with Simulated Annealing, one of the most popular optimization algorithm in use today. The algorithms have been tested on four different digital circuits and the results collated and compared in this paper.
机译:晶体管大小优化是电路设计的一个重要方面。 可以使用手动计算和电路模拟轻松设计小型和非复杂电路。 但是,随着电路的复杂性增加,手动设计变得太难且耗时。 因此,在电路设计领域,自动晶体管尺寸的工具和技术非常重要。 本文的目标是实施遗传模拟退火算法作为晶体管尺寸的工具,并将其与模拟退火的性能进行比较,这是今天最受欢迎的优化算法之一。 该算法已经在四个不同的数字电路上进行了测试,并在本文中进行了并进行了比较。

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