DocumentCode :
2825481
Title :
Design of normal mode helical antenna using neural networks
Author :
Jagadeesh, V.K. ; Kumar, Sahoo Subhendu
Author_Institution :
Dept. of Electron. & Commun. Eng., Coll. of Eng., Trivandrum, India
fYear :
2011
fDate :
18-22 Dec. 2011
Firstpage :
1
Lastpage :
4
Abstract :
Mobile communication requires dual band operation. Normal mode helical antenna is commonly used for dual band frequency operations. The design of normal helical antenna usually done by trial and error procedure. Starting with a standard geometry the geometrical parameters of the helix are adjusted until desired characteristics is obtained. In this paper we present a method to design a dual band helical antenna using Artificial neural networks (ANN). The gain and resonant frequency parameters are estimated for different helix geometries using 4NEC2 software and a database is prepared. Using this database Back Propagation Neural Network is trained with input as geometry parameters and output as gain and frequency parameters. Once the network is trained this BPNN can be used for designing the antenna for a given specification. The simulated results show good agreement with desired specification.
Keywords :
design engineering; helical antennas; mobile communication; multifrequency antennas; neural nets; 4NEC2 software; BPNN; artificial neural networks; database back propagation neural network; dual band frequency operation; dual band helical antenna; dual band operation; helix geometry; mobile communication; normal mode helical antenna; resonant frequency; standard geometry; Databases; Dual band; Geometry; Helical antennas; Neural networks; Resonant frequency; Back propagation Neural networks (BPNN); Helical Antenna; Normal mode helical antenna (NMHA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Electromagnetics Conference (AEMC), 2011 IEEE
Conference_Location :
Kolkata
Print_ISBN :
978-1-4577-1098-8
Type :
conf
DOI :
10.1109/AEMC.2011.6256822
Filename :
6256822
Link To Document :
بازگشت