基于差分进化算法和粒子群优化的低功耗CMOS缓冲链电路自动设计

Bhoomi Thakkar, V. Nayak
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引用次数: 1

摘要

本文将PSO和DE算法及其变体用于缓冲链电路的优化,并对所有算法的结果进行了比较。通过在不同的数学基准函数上对这些算法进行测试,得到了缓冲链电路的最佳参数值,从而减小了模拟输出与优化输出之间的误差,从而获得了最佳的电路性能。进化算法在性能和速度上都优于经典算法。在这项工作中使用了130nm CMOS技术。利用这些参数值,电路模拟器给出了电路的功耗、对称性、上升时间和下降时间等参数值,这些参数值几乎接近缓冲链电路的期望规格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic design of low power CMOS buffer-chain circuit using differential evolutionary algorithm and particle swarm optimization
PSO and DE algorithms and its variants are used for the optimization of a buffer-chain circuit and the results of all the algorithms are compared in this literature. By testing these algorithms on different mathematical benchmark functions the best parameter values of buffer chain circuit are obtained in such a way that it reduces the error between simulated output and optimized output, hence giving the best circuit performance. Evolutionary algorithms are better in performance and speed than the classical methods. 130nm CMOS technology has been used in this work. With the help of these parameter values the circuit simulator gives the values of power consumption, symmetry, rise time and fall time, which are almost closer to the desired specification of the buffer chain circuit.
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