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Reducing a number of full-wave analyses in RBF neural network optimization of complex microwave structures

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2 Author(s)
Murphy, E.K. ; Dept. of Math. Sci., Worcester Polytech. Inst., Worcester, MA, USA ; Yakovlev, V.V.

This paper introduces an original technique of neural network optimization of substantially less computational cost and suitable for viable CAD of complex microwave systems. A number of necessary full-wave simulations are dramatically reduced due to a special objective function and CORS sampling in the dynamic training of the decomposed RBF network. Performance of the algorithm is illustrated by its application to a waveguide band-pass filter and a dielectric resonator antenna; their optimal designs are found from 5-parameter optimizations requiring as little as 167 and 99 analyses, respectively.

Published in:

Microwave Symposium Digest, 2009. MTT '09. IEEE MTT-S International

Date of Conference:

7-12 June 2009