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An Improved Genetic Algorithm for Optimizing EBG Structure With Ultra-Wideband SSN Suppression Performance of Mixed Signal Systems
- Source :
- IEEE Access, Vol 8, Pp 26129-26138 (2020)
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- 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.
- Subjects :
- education.field_of_study
General Computer Science
Computer science
electromagnetic band gap
Population
Crossover
General Engineering
Initialization
Ultra-wideband
Hamming distance
Power integrity
Mixed-signal integrated circuit
Genetic algorithm
genetic algorithm
Electronic engineering
multi objective optimization
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Electrical and Electronic Engineering
Automatic optimization
education
simultaneously switching noise
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....93da128fa41fa3d0438f4f32cf9ac7de