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• W2912120219 abstract "In this research paper, the development of an artificial neural network (ANN) model for the designing of a compact dual-band hybrid fractal antenna (CDHFA) that covers Wireless Medical Telemetry Service and industrial, scientific and medical (ISM) bands are described. The projected CDHFA is designed by using 1.6mm thick, FR4 substrate whose permittivity is 4.4 and obtained by the combination of different fractal geometries. The dimensions of the projected CDHFA are interlinked with each other. A set of 80 CDHFAs with different dimensions is designed to obtain a data dictionary for the implementation of ANN. From the experimental results, it is depicted that the resonant frequencies are 1.4290 and 2.4380 GHz with S(1,1) values −12.4 and −15.72 dB, respectively. A comparison between feed forward back propagation network, generalised regression neural network and desired outputs in terms of average absolute error is also done. The simulation, experimental and ANN results are well matched that indicates the effectiveness and accuracy of the developed ANN model for biomedical applications." @default.
• W2912120219 created "2019-02-21" @default.
• W2912120219 creator A5033892624 @default.
• W2912120219 creator A5073487445 @default.
• W2912120219 date "2019-03-06" @default.
• W2912120219 modified "2023-10-18" @default.
• W2912120219 title "ANN-based design of hybrid fractal antenna for biomedical applications" @default.
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• W2912120219 doi "https://doi.org/10.1080/00207217.2019.1582712" @default.
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