Automated synthesis of a printed dipole antenna with FD-TD and a novel artificial neural network

Author

Delgado, Heriberto J. ; Thursby, Michael H.

Author_Institution

Harris Corp., Melbourne, FL, USA

Volume

4

fYear

2004

fDate

20-25 June 2004

Firstpage

4400

Abstract

A novel artificial neural network (ANN) used in combination with the finite difference time domain method (FD-TD), is presented. Practical applications are illustrated by optimizing the voltage standing wave ratio (VSWR) of a printed dipole antenna. An artificial neural network (ANN) architecture, consisting of a hetero-associative memory utilizing a simple sum number representation, is employed. The number representation revealed insight into a new method of fault tolerant computing. Furthermore, a new randomization process allows synthesizing antenna geometrical parameters. Further work is needed to evaluate the potential of this new paradigm.

Keywords

dipole antennas; fault tolerant computing; finite difference time-domain analysis; microstrip antennas; neural nets; ANN; ANN architecture; FDTD method; VSWR; artificial neural network; automated synthesis; fault tolerant computing; finite difference time domain method; hetero-associative memory; printed dipole antenna; randomization process; sum number representation; voltage standing wave ratio; Artificial neural networks; Dipole antennas; Feeds; Finite difference methods; Geometry; Impedance matching; Microstrip; Network synthesis; Time domain analysis; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium, 2004. IEEE

Print_ISBN

0-7803-8302-8

Type

conf

DOI

10.1109/APS.2004.1330327

Filename

1330327