Data-efficient Minimax quickest change detection with composite post-change distribution

Taposh Banerjee, Venugopal V. Veeravalli

Research output: Contribution to journalArticlepeer-review


The problem of quickest change detection is studied, where there is an additional constraint on the cost of observations used before the change point and where the post-change distribution is composite. Minimax formulations are proposed for this problem. It is assumed that the post-change family of distributions has a member which is least favorable in a well-defined sense. An algorithm is proposed in which ON-OFF observation control is employed using the least favorable distribution, and a generalized likelihood ratio-based approach is used for change detection. Under additional conditions on the post-change family of distributions, it is shown that the proposed algorithm is asymptotically optimal, uniformly for all possible post-change distributions.

Original languageEnglish (US)
Article number7163605
Pages (from-to)5172-5184
Number of pages13
JournalIEEE Transactions on Information Theory
Issue number9
StatePublished - Sep 1 2015


  • Asymptotic optimality
  • CuSum
  • exponential family
  • generalized likelihood ratio
  • least favourable distribution
  • minimax
  • observation control
  • quickest change detection
  • unknown post-change distribution

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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