How complex is a random picture?

Frank Aurzada, Mikhail Lifshits

Research output

Abstract

We study the amount of information that is contained in “random pictures” by which we mean the sample sets of a Boolean model. To quantify the notion “amount of information” two closely connected questions are investigated: on the one hand, we study the probability that a large number of balls is needed for a full reconstruction of a Boolean model sample set. On the other hand, we study the quantization error of the Boolean model w.r.t. the Hausdorff distance as a distortion measure.

Original languageEnglish
Pages (from-to)133-161
Number of pages29
JournalJournal of Complexity
Volume53
DOIs
Publication statusPublished - Aug 2019

Scopus subject areas

  • Control and Optimization
  • Applied Mathematics
  • Mathematics(all)
  • Numerical Analysis
  • Algebra and Number Theory
  • Statistics and Probability

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