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Application of neural networks in space‐mapping optimization of microwave filters
Author(s) -
Wang Ying,
Yu Ming,
Kabir Humayun,
Zhang QiJun
Publication year - 2012
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.20572
Subject(s) - space mapping , microwave , dimension (graph theory) , filter (signal processing) , artificial neural network , sensitivity (control systems) , representation (politics) , waveguide filter , coupling (piping) , computer science , electronic engineering , algorithm , prototype filter , filter design , topology (electrical circuits) , mathematics , engineering , artificial intelligence , telecommunications , mechanical engineering , politics , law , political science , pure mathematics , computer vision , combinatorics
In this paper, a design methodology combining coupling matrix representation of filters, neural models and space‐mapping techniques is presented for further enhancement of optimization efficency of microwave filters. Neural models are developed for both initial dimension generation and design parameter sensitivity analysis. Combining neural models of filter substructures with space‐mapping optimization, the total number of EM simulations of the complete filter structure is significantly reduced. The improvement in efficiency over conventional method is demonstrated using simulation and measurement results of both end‐coupled and side‐coupled waveguide dual‐mode pseudo‐elliptic filters. The total CPU times for design and optimization are reduced by 50% to 70 %.© 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.