NDLI: An accurate computation method based on artificial neural networks with different learning algorithms for resonant frequency of annular ring microstrip antennas

Content Provider	Springer Nature Link
Author	Akdagli, Ali Kayabasi, Ahmet
Copyright Year	2014
Abstract	An annular ring compact microstrip antenna (ARCMA) constructed by loading a circular slot in the center of the circular patch antenna is a popular microstrip antenna due to its favorable properties. In this study, a method based artificial neural networks (ANNs) has been firstly applied for the computing the resonant frequency of ARCMAs. Multilayered perceptron model based on feed forward back propagation ANN has been utilized, and the constructed model have been separately trained with 8 different learning algorithms to achieve the best results regarding the resonant frequency of ARCMAs at dominant mode. To this end, the resonant frequencies of 80 ARCMAs with varied dimensions and electrical parameters in accordance with UHF band covering GSM, LTE, WLAN and WiMAX applications were simulated with a robust numerical electromagnetic computational tool, $$\hbox {IE3D}^\mathrm{TM}$$ , which is based on method of moment. Then, ANN model was constructed with the simulation data, by using 70 ARCMAs for training and the remaining 10 for test. As the performances of the 8 learning algorithms are compared with each other, the best result is obtained with Levenberg–Marquardt algorithm. The proposed ANN model were confirmed by comparing with the suggestions reported elsewhere via measurement data published earlier in the literature, and they have further validated on an ARCMA fabricated in this study. The results achieved in this study show that ANN model learning with LM algorithm can be successfully used to compute the resonant frequency of ARCMAs without involving any sophisticated methods.
Starting Page	1014
Ending Page	1019
Page Count	6
File Format	PDF
ISSN	15698025
Journal	Journal of Computational Electronics
Volume Number	13
Issue Number	4
e-ISSN	15728137
Language	English
Publisher	Springer US
Publisher Date	2014-09-23
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Annular ring compact microstrip antenna Resonant frequency Artificial neural network (ANN) Learning algorithms Levenberg–Marquardt algorithm ApplicationMathematics/Computational Methods of Engineering Electrical Engineering Theoretical, Mathematical and Computational Physics Optical and Electronic Materials Mechanical Engineering
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering Modeling and Simulation

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