基于进化算法的低功耗CMOS两级比较器优化设计方法

K. B. Maji, S. Choudhury, R. Kar, D. Mandal, S. Ghoshal
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引用次数: 1

摘要

本文提出了一种采用单纯形粒子群优化(simplex - pso)方法设计CMOS两级比较器(TSC)的进化方法。它是一种基于群体智能的进化计算方法。单纯形优化算法是将Nelder-Mead单纯形算法(NMSM)和粒子群优化算法(PSO)混合而成的一种不带速度项的算法。它专注于面积、功率的优化,并以最小的计算时间改进了CMOS两级比较器的所有其他性能参数。与差分进化(DE)、和谐搜索(HS)等方法不同,基于Simplex-PSO的电路优化技术克服了其固有的过早收敛和停滞的缺点。仿真结果表明,Simplex-PSO优化设计的两级比较器电路占用最小的MOS面积和最小的功耗。所得结果优于已有文献。采用0.35μm工艺的Cadence光谱电路模拟器进行仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An evolutionary algorithm based approach for optimal design of low power CMOS two-stage comparator
This work presents an evolutionary approach to design CMOS Two-Stage Comparator (TSC) using simplex particle swarm optimization (Simplex-PSO) method. It is a swarm intelligent based evolutionary computation method. Simplex-PSO is the hybridization of Nelder-Mead Simplex method (NMSM) and Particle Swarm Optimization (PSO) without the velocity term. It has focused on the optimization of the area, power and has improved all other performance parameters of the CMOS two-stage comparator with minimum computational time. The proposed Simplex-PSO based circuit optimization technique is relieved from the inherent drawbacks of premature convergence and stagnation, unlike Differential Evolution (DE), Harmony Search (HS). The simulation results prove that Simplex-PSO yields optimally designed two-stage comparator circuit which occupies the least MOS area and dissipates the least power. It provides better results than those of the reported works. Simulation is carried out by Cadence spectra circuit simulator using 0.35μm technology.
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