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<p>The dual-frequency resonance antenna design presented in this paper was optimized with a neural network tool and integrated into a slotted microstrip patch. With resonance frequencies at 2.25&#xa0;GHz and 6.63&#xa0;GHz, respectively, the antenna provides 3.50% bandwidth at 200&#xa0;MHz for the lower band (return loss: − 14.65&#xa0;dB) and 19.20% bandwidth at 420&#xa0;MHz for the upper band. IE3D simulation software was used for development and analysis, and an artificial neural network (ANN) with the Levenberg–Marquardt method was used for optimization. The ANN model's dependability was confirmed by its average error of only 0.27% when trained with different antenna parameters. The performance of the antenna was confirmed by the near match between the simulated and practical prototypes.</p>

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Optimization and Bandwidth Analysis of Simple Symmetrical Maze Pattern Shaped Slotted Microstrip Patch Antenna with Artificial Neural Network

  • 期刊论文

  • 发表日期：

    2025年2月7日

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  • Om Singh,
  • Shahanaz Ayub,
  • S. K. Sriwas

摘要

The dual-frequency resonance antenna design presented in this paper was optimized with a neural network tool and integrated into a slotted microstrip patch. With resonance frequencies at 2.25 GHz and 6.63 GHz, respectively, the antenna provides 3.50% bandwidth at 200 MHz for the lower band (return loss: − 14.65 dB) and 19.20% bandwidth at 420 MHz for the upper band. IE3D simulation software was used for development and analysis, and an artificial neural network (ANN) with the Levenberg–Marquardt method was used for optimization. The ANN model's dependability was confirmed by its average error of only 0.27% when trained with different antenna parameters. The performance of the antenna was confirmed by the near match between the simulated and practical prototypes.