Publisher： John Wiley & Sons Inc
E-ISSN： 1099-047x|25|9|769-779
ISSN： 1096-4290
Source： INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING (ELECTRONIC), Vol.25, Iss.9, 2015-11, pp. : 769-779
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Abstract
ABSTRACTNeural networks play an important role for designing the parametric model of electromagnetic structures. The current neural network methods are unfit for a circuit model with many input variables because it is costly to extract a large number of the training data and test data to complete the highly nonlinear mapping approximation. This article proposes a new neural network modeling method—the multidimensional neural network model, which can be used to solve the issue of multivariable radiofrequency and microwave passive device modeling. The entire multidimensional neural network modeling problem is simplified into a set of neural network submodels through decomposition method. Then the submodels are combined into an equivalent model, and the final entire model is produced through the neural‐network mapping model developed with the submodels and equivalent model. A microstrip hairpin filter model is developed using the proposed method. The simulation results show the correctness and the effectivity of the proposed method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:769–779, 2015.
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