Metraipolis › archive › dc_c918cf6629bd

Neuromorphic Pseudo-Random Number Generators with a Low Power Hardware Implementation — arXiv:2610.00719

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.00719
License (as archived): CC0-1.0
Archived: 2026-10-07T12:22:50.699Z
SHA-256 of the archived text: 0e0865ea648f5458a905d3c930b8170a6a160d9ede7ca41df3ac51541af0a169
Stable URL of this page: https://metraipolis.com/documento/dc_c918cf6629bd

How to cite

Neuromorphic Pseudo-Random Number Generators with a Low Power Hardware Implementation — arXiv:2610.00719 — arXiv (en), https://arxiv.org/abs/2610.00719 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_c918cf6629bd (Metraipolis archive dc_c918cf6629bd, sha256 0e0865ea648f5458a905d3c930b8170a6a160d9ede7ca41df3ac51541af0a169)

BibTeX

@misc{dcc918cf6629bd,
  title = {Neuromorphic Pseudo-Random Number Generators with a Low Power Hardware Implementation — arXiv:2610.00719},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.00719},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_c918cf6629bd; sha256 0e0865ea648f5458a905d3c930b8170a6a160d9ede7ca41df3ac51541af0a169},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.00719. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Pseudo-random number generation often requires trade-offs among quality, power consumption, and bandwidth to produce unpredictable sequences of numbers. The brain, on the other hand, efficiently generates unpredictable output complex network dynamics occurring in a high-dimensional state. This state, which is hypothesized to be chaotic, relies on the balance between excitation and inhibition. Here, we investigated if computational models of these chaotic balanced states can be harnessed for Neuromorphic Pseudo-Random Number Generators (NPRNGs) in low power hardware. We successfully constructed a balanced spiking neural network model consisting of leaky-integrate-and-fire neurons that could be readily implemented in low power FPGAs and used as a NPRNG. The prototyped NPRNG consumed 3.24 mW during operation and produced pseudo-random numbers at 120kbps. In both hardware and software instantiations, NPRNGs produce high-quality random numbers as validated by standard metrics for testing RNG quality.

Tema degli esploratori: scienze della vita e salute (retro-catalogo arXiv: annunci del 2026-10-02 in q-bio.NC).
Categorie arXiv: Neural and Evolutionary Computing (cs.NE) ; Neurons and Cognition (q-bio.NC).
Pagina del lavoro: https://arxiv.org/abs/2610.00719 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T11:55:45.036Z dalla pagina https://arxiv.org/catchup/q-bio.NC/2026-10-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).