A hybrid genetic algorithm method for optimizing analog circuits

S. Papadopoulos, R. Mack, R. Massara
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引用次数: 15

Abstract

An approach is presented for the automated sizing of analog circuits based upon a combination of a genetic algorithm (GA) with a least squares (Gauss-Newton) gradient search. The method combines the global-search properties of the GA with the fast local convergence properties of the least squares method to produce a circuit design from random initial component values in a reduced time compared to the application of a direct GA method, or a restart least squares algorithm. Results are presented to demonstrate the application of the method in the design of both passive and active circuits.
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一种优化模拟电路的混合遗传算法
提出了一种基于遗传算法和最小二乘高斯-牛顿梯度搜索相结合的模拟电路自动尺寸确定方法。该方法将遗传算法的全局搜索特性与最小二乘法的快速局部收敛特性相结合,与直接遗传算法或重新启动最小二乘法相比,可以在更短的时间内从随机初始元件值生成电路设计。结果表明了该方法在无源和有源电路设计中的应用。
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