Multi-parametric ANN modelling for interference rejection in UWB antennas

被引：11

作者：

Sarkar, Debanjali ^{[1
]}

Khan, Taimoor ^{[1
]}

Laskar, Rabul H. ^{[1
]}

机构：

[1] Natl Inst Technol, Elect & Commun Engn, Silchar, India

来源：

INTERNATIONAL JOURNAL OF ELECTRONICS | 2020年 / 107卷 / 12期

关键词：

Artificial neural network (ANN); rectangular monopole antenna; triple notch; ultra-wide Band (UWB); U-shaped slots; RESONANT-FREQUENCY; NEURAL-NETWORK; DESIGN;

D O I：

10.1080/00207217.2020.1756449

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：2068 / 2083

页数：16

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