{
  "id": "1609.08821",
  "version": "v1",
  "published": "2016-09-28T08:47:54.000Z",
  "updated": "2016-09-28T08:47:54.000Z",
  "title": "Model Reduction from Partial Observations",
  "authors": [
    "C. Herzet",
    "A. Drémeau",
    "P. Héas"
  ],
  "categories": [
    "math.NA"
  ],
  "abstract": "This paper deals with model order reduction of parametric partial differential equations (PPDE). We consider the specific setup where the solutions of the PPDE are only observed through a partial observation operator and address the task of finding a good approximation subspace of the solution manifold. We provide and study several tools to tackle this problem. We first identify the best worst-case performance achievable in this setup and propose simple procedures to approximate this optimal solution. We then provide, in a simplified setup, a theoretical analysis relating the achievable reduction performance to the choice of the observation operator and the prior knowledge available on the solution manifold.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-09-28T08:47:54.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "model reduction",
      "parametric partial differential equations",
      "solution manifold",
      "model order reduction",
      "partial observation operator"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}