Comparison of two optimization techniques for the estimation of complex permittivities of multilayered structures using waveguide measurements

In this paper, two separate techniques, i.e., sequential quadratic programming (SQP) and a genetic algorithm (GA), were used to estimate the complex permittivity of each layer in a multilayer composite structure. The relative performance of the algorithms was characterized by applying each algorithm...

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Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 2005-10, Vol.53 (10), p.3251-3259
Main Authors: Baginski, M.E., Faircloth, D.L., Deshpande, M.D.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Circuit properties
Complex permittivity
Computer errors
Dielectric materials
Dielectric measurements
Electric, optical and optoelectronic circuits
Electromagnetic waveguides
Electronics
Error functions
Exact sciences and technology
Frequency
Genetic algorithm (GA)
Genetic algorithms
Microwave circuits, microwave integrated circuits, microwave transmission lines, submillimeter wave circuits
Microwave integrated circuits
MMICs
multilayered substrate
Multilayers
Nonhomogeneous media
permittivity extraction
Permittivity measurement
Quadratic programming
sequential quadratic programming (SQP)
Waveguides
X-band
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Summary:In this paper, two separate techniques, i.e., sequential quadratic programming (SQP) and a genetic algorithm (GA), were used to estimate the complex permittivity of each layer in a multilayer composite structure. The relative performance of the algorithms was characterized by applying each algorithm to one of three different error functions. Computer generated S-parameter data sets were initially used in order to establish the achievable accuracy of each algorithm. Based on these data sets and S-parameter measurements of single and multilayer samples obtained using a standard X-band waveguide procedure, the GA was determined to be the more robust algorithm in terms of minimizing rms error of measured/generated and formulated S-parameters. The GA was found to perform exceptionally well for all cases considered, whereas SQP, although a more computationally efficient method, was somewhat limited for two error function choices due to local minima trapping.
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2005.855133