Capacity/Storage Tradeoff in High-Dimensional Identification Systems

  title={Capacity/Storage Tradeoff in High-Dimensional Identification Systems},
  author={Ertem Tuncel},
  journal={2006 IEEE International Symposium on Information Theory},
The asymptotic tradeoff between the number of distinguishable objects and the necessary storage space (or equivalently, the search complexity) in an identification system is investigated. In the discussed scenario, high-dimensional (and noisy) feature vectors extracted from objects are first compressed and then enrolled in the database. When the user submits a random query object, the extracted noisy feature vector is compared against the compressed entries, one of which is output as the… CONTINUE READING
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