Multi-parametric ANN modelling for interference rejection in UWB antennas

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.