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Fault tolerance estimation in digital circuits with visualised generative networks

arXiv 2605.15212 ↗First posted 9 May 2026cs.AR cs.AI cs.CEcited by 0

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Abstract (arXiv)

We propose a new numerical method to estimate the fault tolerance of failure modes in digital circuit structures with a generative network sampling technique. From a random input of generated bitwise configurations of ideally digitalised analog currents in the digital circuit design with classical logical gates, expected output currents are compared to the realistic signals of a numerical experiment at the discriminator part of the Generative Adversarial Network (GAN) to calculate the deviation from ideal digital electronic signals, including various error modes, such as missing or interchanged logical devices. From the present analysis of a representation of the GAN in terms of complex variables, it is possible to evaluate the robustness in electronic designs by differentiating the impact of failure modes associated with different classical logical elements in the circuit.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 22 references that are in the map. First posted on arXiv 9 May 2026.

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References · 3

  1. 2020Hopfield Networks is All You Needcited by 475
  2. 2023In search of dispersed memories: Generative diffusion models are associative memory networkscited by 44
  3. 2025Secure Text Mail Encryption with Generative Adversarial Networkscited by 1

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