Abstract：A novel space mapping algorithm with high convergence is presented that improves the parameters mapping from surrogate model to fine model. By adding the process of coarse model parameter selection, it avoids false convergence in the optimization of surrogate model and speeds up the approximation between fine model and design object. No extra fine model evaluation is necessary in the parameter selection process, the optimization efficiency is improved. In this paper, a hairpin filter is designed and is compared with previous implicit space mapping algorithm, the results are better than the design specifications. The new algorithm is verified faster and more efficient.
邢连发, 雷振亚, 谢拥军, 李平, 山团彪, 石晶. 新型高收敛隐式空间映射算法设计微波滤波器[J]. 电子与信息学报, 2011, 33(3): 744-748.
Xing Lian-Fa, Lei Zhen-Ya, Xie Yong-Jun, Li Ping, Shan Tuan-Biao, Shi Jing. A New Implicit Space Mapping with High Convergence for Microwave Filter Design. , 2011, 33(3): 744-748.
2011, Vol. 33 
