An Improved Genetic Algorithm for Optimizing EBG Structure With Ultra-Wideband SSN Suppression Performance of Mixed Signal Systems

被引：4

作者：

Zhu, Haoran ^{[1
,2
]}

Wang, Jiabao ^{[1
]}

Sun, Yufa ^{[1
]}

Wu, Xian-Liang ^{[1
]}

机构：

[1] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Peoples R China

[2] Southeast Univ, State Key Lab Millimeter Waves, Nanjing 210096, Peoples R China

来源：

IEEE ACCESS | 2020年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Automatic optimization; electromagnetic band gap; genetic algorithm; multi objective optimization; simultaneously switching noise; OPTIMIZATION;

D O I：

10.1109/ACCESS.2020.2971355

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, an improved genetic algorithm (GA) for automatically optimizing electromagnetic bandgap (EBG) structure with good power integrity performance is presented. The traditional GA is improved in several ways including Hamming Distance initialization, elite selection and non-repeating crossover, which can generate initial population charactering solution space in detail, increase crossover efficiency, and accelerate convergence. Furthermore, an EBG structure for power distribution network is optimized with the presented GA method to improve the performances of power integrity. The simultaneous switching noise propagation can be prohibited from 0.38 GHz to 20 GHz with a suppression level of -60 dB. Good agreements between the measured results and the simulation ones are observed.

引用

页码：26129 / 26138

页数：10

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