{
  "id": "1405.0237",
  "version": "v1",
  "published": "2014-05-01T17:51:07.000Z",
  "updated": "2014-05-01T17:51:07.000Z",
  "title": "An RIP-based approach to $ΣΔ$ quantization for compressed sensing",
  "authors": [
    "Joe-Mei Feng",
    "Felix Krahmer"
  ],
  "comment": "11 pages",
  "categories": [
    "cs.IT",
    "math.IT"
  ],
  "abstract": "In this paper, we provide a new approach to estimating the error of reconstruction from $\\Sigma\\Delta$ quantized compressed sensing measurements. Our method is based on the restricted isometry property (RIP) of a certain projection of the measurement matrix. Our result yields simple proofs and a slight generalization of the best-known reconstruction error bounds for Gaussian and subgaussian measurement matrices.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2014-05-01T17:51:07.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "compressed sensing",
      "rip-based approach",
      "result yields simple proofs",
      "quantization",
      "best-known reconstruction error bounds"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "doi": "10.1109/LSP.2014.2336700",
      "journal": "IEEE Signal Processing Letters",
      "year": 2014,
      "month": "Nov",
      "volume": 21,
      "number": 11,
      "pages": 1351
    },
    "note": {
      "typesetting": "TeX",
      "pages": 11,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2014ISPL...21.1351F"
    }
  }
}