NFDTD Concept

RK Mishra, Peter Hall

Research output: Contribution to journalArticle

5 Citations (Scopus)


This paper combines artificial neural network (ANN) technique with the finite difference time domain (FDTD) technique. A detailed illustration of the concept, in this paper, uses a 3-8-1 feedforward artificial neural network (FF-ANN) for approximating the Z-component of the electric field in a rectangular waveguide in TM mode. The FDTD equation (i.e., the two-dimesnional (2-D) wave equation in discrete form) is embedded into the cost function of the ANN. Results of implementing this technique in a one-dimensional (1-D) transmission line resonator are also provided with 4-10-1 FF-ANN. The result of the leap-frog algorithm implementation, for this 1-D problem using a (3-6-1) x (3-6-1) hybrid FF-ANN, is also provided. The neural-finite difference time domain (NFDTD) results are compared with those of the traditional FDTD.
Original languageEnglish
Pages (from-to)484-490
Number of pages7
JournalIEEE Transactions on Neural Networks
Issue number2
Publication statusPublished - 1 Mar 2005


  • waveguide
  • neural network
  • resonator
  • finite difference time domain (FDTD)
  • neural-finite difference time domain (NFDTD)


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