{
  "id": "1902.08428",
  "version": "v1",
  "published": "2019-02-22T10:35:53.000Z",
  "updated": "2019-02-22T10:35:53.000Z",
  "title": "Convergence Rate of Empirical Spectral Distribution of Random Matrices from Linear Codes",
  "authors": [
    "Chin Hei Chan",
    "Vahid Tarokh",
    "Maosheng Xiong"
  ],
  "categories": [
    "math.PR",
    "cs.IT",
    "math.IT"
  ],
  "abstract": "It is known that the empirical spectral distribution of random matrices obtained from linear codes of increasing length converges to the well-known Marchenko-Pastur law, if the Hamming distance of the dual codes is at least 5. In this paper, we prove that the convergence in probability is at least in the order of $n^{-1/4}$ where $n$ is the length of the code.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2019-02-22T10:35:53.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "60B20",
      "94B05"
    ],
    "keywords": [
      "empirical spectral distribution",
      "linear codes",
      "random matrices",
      "convergence rate",
      "well-known marchenko-pastur law"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}