Fractal Localized EBG Structure Intelligently Optimized by K-GRNN and GA Method for Signal and Power Integrity

Abstract

In this article, a miniaturized fractal localized electromagnetic bandgap (EBG) structure for signal and power integrities is intelligently modeled and optimized with a K-means generalized regression neural network (GRNN) and genetic algorithm (GA). The proposed EBG structure is realized with a combination of L-shaped bridge and slit patch, which is inserted by a Koch fractal resonator with a smaller electric length. To minimize the influence of the period EBG structure on the signal integrity, the fractal structure is only designed on the noise source and sensitive area with localized topology. In comparison with the traditional GRNN method, the modeling precision for discontinuous points such as resonance and antiresonance peaks of the scattering parameter curve can be improved with K-means-GRNN. Finally, a power distribution network sample with the proposed localized fractal EBG structure is designed with a steep suppression level of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> 50 dB from 0.36 to 20 GHz.