{
  "id": "1907.01200",
  "version": "v1",
  "published": "2019-07-02T07:03:32.000Z",
  "updated": "2019-07-02T07:03:32.000Z",
  "title": "A New Cyclic Gradient Method Adapted to Large-Scale Linear Systems",
  "authors": [
    "Qinmeng Zou",
    "Frederic Magoules"
  ],
  "journal": "17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), 2018, IEEE",
  "categories": [
    "math.NA",
    "cs.NA"
  ],
  "abstract": "This paper proposes a new gradient method to solve the large-scale problems. Theoretical analysis shows that the new method has finite termination property for two dimensions and converges R-linearly for any dimensions. Experimental results illustrate first the issue of parallel implementation. Then, the solution of a large-scale problem shows that the new method is better than the others, even competitive with the conjugate gradient method.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2019-07-02T07:03:32.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "large-scale linear systems",
      "cyclic gradient method",
      "large-scale problem",
      "experimental results illustrate first",
      "conjugate gradient method"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}