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Neural network with knowledge‐based neurons for the modeling of crossover discontinuities in stripline circuits
Author(s) -
Hong J. S.,
Wang B. Z.,
Hu B. J.,
Liu Y. W.
Publication year - 2002
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.10387
Subject(s) - stripline , crossover , classification of discontinuities , artificial neural network , electronic circuit , microwave , electronic engineering , perceptron , set (abstract data type) , engineering , multilayer perceptron , computer science , algorithm , electrical engineering , artificial intelligence , telecommunications , mathematics , mathematical analysis , programming language
Abstract A novel three‐layer neural network with knowledge‐based neurons in hidden layer (NNKBN) has been applied to model the crossover discontinuities in stripline circuits. The NNKBN model is electromagnetically developed with a set of data that are produced by the full‐wave finite‐difference–time‐domain method. Numerical experiments show that the NNKBN model has many advantages over the conventional multilayer perceptron model. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 34: 107–109, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10387