{
  "annotation_id": "30704cf0-d656-46b9-897e-455d9f794b03",
  "date_created": "2026-03-02T18:01:11.454000Z",
  "date_modified": "2026-03-02T18:01:11.454000Z",
  "file_hash": "11b312890a0455cf08ad9608af7650726d85e5f98142fbddc2e93ff7c3609139",
  "private": false,
  "record": {
    "abstract": "Previous preliminary results on the application of knowledge networks to\nnoise reduction in stationary harmonic and weakly chaotic signals are extended\nto more general cases. The formalism gives a novel algorithm from which\nstatistical tests for the identification of deterministic behavior in noisy\nstationary time series can be constructed.",
    "arxiv_id": "physics/0609048",
    "authors": [
      "Arturo Berrones"
    ],
    "categories": [
      "physics.data-an",
      "cond-mat.dis-nn"
    ],
    "title": "Knowledge Network Approach to Noise Reduction",
    "url": "https://arxiv.org/abs/physics/0609048"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4881dde3-725c-4647-a88f-6ee1ef4b77f1",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}