{
  "annotation_id": "7297b995-a111-45f7-93fc-88f344953d83",
  "date_created": "2026-03-02T18:01:25.129000Z",
  "date_modified": "2026-03-02T18:01:25.129000Z",
  "file_hash": "6f425a403e25dba3fbb0093835bfa8050c11858c26d0bc80545f21c862297029",
  "private": false,
  "record": {
    "abstract": "A set of fixed points of the Hopfield type neural network was under\ninvestigation. Its connection matrix is constructed with regard to the Hebb\nrule from a highly symmetric set of the memorized patterns. Depending on the\nexternal parameter the analytic description of the fixed points set had been\nobtained. And as a conclusion, some exact results of Hopfield neural networks\nwere gained.",
    "arxiv_id": "physics/9907042",
    "authors": [
      "Hong-Liang Lu",
      "Xi-Jun Qiu"
    ],
    "categories": [
      "physics.bio-ph",
      "q-bio"
    ],
    "title": "Some Exact Results of Hopfield Neural Networks and Applications",
    "url": "https://arxiv.org/abs/physics/9907042"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "238387b1-1e00-461e-bace-6490d126c145",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}