{
  "annotation_id": "31e30901-a27f-42ad-b06e-611418c1007d",
  "date_created": "2026-03-02T18:00:46.931000Z",
  "date_modified": "2026-03-02T18:00:46.931000Z",
  "file_hash": "22d5afea81346c9914b723ec6d4ad2aa138ecb2fdad232df8c32e5ba39a4db0d",
  "private": false,
  "record": {
    "abstract": "An efficient technique is introduced for model inference of complex nonlinear\ndynamical systems driven by noise. The technique does not require extensive\nglobal optimization, provides optimal compensation for noise-induced errors and\nis robust in a broad range %of parameters of dynamical models. It is applied to\nclinically measured blood pressure signal for the simultaneous inference of the\nstrength, directionality, and the noise intensities in the nonlinear\ninteraction between the cardiac and respiratory oscillations.",
    "arxiv_id": "physics/0310062",
    "authors": [
      "V. N. Smelyanskiy",
      "D. A. Timucin",
      "A. Bandrivskyy",
      "D. G. Luchinsky"
    ],
    "categories": [
      "physics.data-an",
      "cond-mat.stat-mech",
      "physics.bio-ph"
    ],
    "title": "Model reconstruction of nonlinear dynamical systems driven by noise",
    "url": "https://arxiv.org/abs/physics/0310062"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e83e8808-0dd2-46cb-bcdd-913510b14897",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}