ANN and IFS based wearable hybrid fractal antenna with DGS for S, C and X band application

Abstract

This paper presents the design and analysis of Wearable Hybrid Fractal Antenna (WHFA) with Defected Ground Structure (DGS) using Artificial Neural Network (ANN) and Iterative Function System (IFS). The proposed antenna is useful for ISM band (Industrial Scientific and Medical), Bluetooth, Satellite communication, and RFID (Radio Frequency Identification) applications. The dimensions of the defected ground plane varied to use optimization techniques for achieving the desired gain, bandwidth at the resonant frequency of the antenna. The comparison of the outcomes of two algorithms Feeds Forward Back Propagation Network (FFBPN) and ELMAN Back Propagation Network (EBPN) with the desired outcomes is done in terms of mean square error. The WHFA with Koch-Meander slot gives the 178 MHz, 4.75 MHz, and 334 MHz bandwidth, gain 8.61 dB, 3.92 dB, and 5.38 dB at resonant frequencies 2.53 GHz, 4.9 and 7.6 GHz respectively. The prototype of the proposed antenna made on a jean substrate with relative permittivity 1.7, height 1 mm, and loss tangent is 0.025. Simulated ANN and measured results are compared and found in agreement with each other.