Neural network with knowledge‐based neurons for the modeling of crossover discontinuities in stripline circuits | Zendy

Hong J. S. | Zendy; Wang B. Z. | Zendy; Hu B. J. | Zendy; Liu Y. W. | Zendy

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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

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

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