Design of rectangular microstrip patch antenna based on Artificial Neural Network algorithm

Author

Singh, Bablu Kumar

Author_Institution

ECE, Jodhpur Inst. of Eng. & Technol., Jodhpur, India

fYear

2015

fDate

19-20 Feb. 2015

Firstpage

6

Lastpage

9

Abstract

The Design of Rectangular Microstrip Patch Antenna using Artificial Neural Network (ANN) has been presented. This paper used Feed Forward Back Propagation Algorithm (FFBPN), Resilient Back-propagation (RPROP), Levenberg-Marquardt (LM) and Radial Basis functions (RBF) of ANN to obtain the resonant frequency of rectangular microstrip patch antenna. The model of ANN algorithm was developed and implemented in MATLAB which convert the parameters containing dielectric constant, substrate thickness, width and length of patch for obtain resonant frequency of antenna and results obtained from these models are compared with standard formula. The results obtained through these algorithms shows very good agreement with the experimental results available in literature.

Keywords

antenna radiation patterns; backpropagation; microstrip antennas; permittivity; radial basis function networks; rectangular waveguides; telecommunication computing; ANN radial basis function; LM; Levenberg-Marquardt; RPROP; artificial neural network RBF algorithm; dielectric constant; feedforward backpropagation algorithm; patch length; patch width; rectangular microstrip patch antenna design; resilient backpropagation; resonant frequency; substrate thickness; Algorithm design and analysis; Artificial neural networks; Mathematical model; Microstrip; Microstrip antennas; Patch antennas; Signal processing algorithms; ANN; FFBPN; LM; MATLAB; Microstrip Antenna; RBF; RPROP;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4799-5990-7

Type

conf

DOI

10.1109/SPIN.2015.7095291

Filename

7095291