Multi-parametric ANN modelling for interference rejection in UWB antennas. Issue 12 (1st December 2020)

• Record Type: Journal Article
• Authors: Sarkar, Debanjali; Khan, Taimoor; Laskar, Rabul H.
• Is Part Of: International journal of electronics. Volume 107:Issue 12(2020)
• Page Start: 2068
• Page End: 2083
• Publication Date: 2020-12-01
• Subjects: Artificial neural network (ANN) -- rectangular monopole antenna -- triple notch -- ultra-wide Band (UWB) -- U-shaped slots; Electronics -- Periodicals; Electronic control -- Periodicals; 621.381
• DOI: 10.1080/00207217.2020.1756449
• Languages: English
• ISSNs: 0020-7217

Abstract

ABSTRACT: In this paper, a multi-parametric analysis modelling for an ultra-wideband (UWB) antenna using artificial neural networks is proposed to predict both the UWB impedance bandwidth and multi-band notch frequencies. Two different neural models are implemented and tested using eight different algorithms. Neural model with two hidden layers having testing mean square error as 27.51 kHz proved to be an efficient one. The effectiveness of the optimised models is further validated using an additional dataset which has not been used during training and/or testing phases. A prototype is fabricated and characterised. Close agreement between simulated and experimental results is validated for the authenticity of the suggested work.