@article{4661,
  author = {Ricardo Rodríguez Jorge},
  title = {Designing a Complete Filter for AI-Assisted or Inverse-Designed Wideband BPF},
  journal = {Journal of Electronic Systems},
  year = {2025},
  volume = {16},
  number = {1},
  doi = {https://doi.org/10.6025/jes/2026/16/1/1-16},
  url = {https://www.dline.info/jes/fulltext/v16n1/jesv16n1_1.pdf},
  abstract = {This paper presents an AI-assisted inverse design methodology for a compact, ultra wideband microstrip
bandpass filter (BPF) that eliminates the need for conventional resonator topologies. Unlike traditional
approaches relying on stepped-impedance resonators, stubs, or defected ground structures, the proposed
design employs a pixelated conductive region optimized directly from electromagnetic performance
objectives using artificial intelligence. The filter architecture consists of two 50- microstrip feedlines coupled
through a 10 mm × 10 mm square domain discretized into a 20 × 20 binary pixel grid, fabricated on a Rogers
RO4350B substrate. A convolutional neural network surrogate model accelerates the optimization process
by over two orders of magnitude, enabling efficient exploration of the topology space while enforcing
fabrication constraints such as minimum feature size and metal continuity. Full-wave simulations
demonstrate a continuous passband from 3 to 10 GHz (fractional bandwidth >100%), in-band insertion loss
below 1.2 dB, return loss better than 15 dB, and stopband rejection exceeding 40 dB. Parametric sensitivity
analyses confirm robustness against ±5% variation in pixel fill ratio, ±3% deviation in substrate permittivity,
and typical feedline width tolerances highlighting practical manufacturability. The AI-discovered geometry
intrinsically integrates resonance generation, impedance matching, and transmission zero formation within
a single planar region, achieving high performance in an electrically compact footprint (<0.25g × 0.25
g). This work establishes inverse electromagnetic design as a scalable and powerful alternative to classical
synthesis techniques, with potential extensions to multi band and reconfigurable RF front end components.},
}