Spice Model Generation from EM Simulation Data Using Integer Coded Genetic Algorithms

Author(s):  
Jens Werner ◽  
Lars Nolle
2017 ◽  
Vol 25 (6) ◽  
pp. 1821-1830 ◽  
Author(s):  
Jaehyun Seo ◽  
Sangheon Lee ◽  
Kwangmin Kim ◽  
Sooeun Lee ◽  
Hyunsang Hwang ◽  
...  

2015 ◽  
Vol 63 (3) ◽  
pp. 781-789
Author(s):  
S. Koziel ◽  
A. Bekasiewicz

Abstract This paper addresses computationally feasible multi-objective optimization of antenna structures. We review two recent techniques that utilize the multi-objective evolutionary algorithm (MOEA) working with fast antenna replacement models (surrogates) constructed as Kriging interpolation of coarse-discretization electromagnetic (EM) simulation data. The initial set of Pareto-optimal designs is subsequently refined to elevate it to the high-fidelity EM simulation accuracy. In the first method, this is realized point-by-point through appropriate response correction techniques. In the second method, sparsely sampled high-fidelity simulation data is blended into the surrogate model using Co-kriging. Both methods are illustrated using two design examples: an ultra-wideband (UWB) monocone antenna and a planar Yagi-Uda antenna. Advantages and disadvantages of the methods are also discussed.


Author(s):  
Canzhong He ◽  
James Victory ◽  
Yunpeng Xiao ◽  
Herbert De Vleeschouwer ◽  
Elvis Zheng ◽  
...  
Keyword(s):  

1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document