Dynamic context-aware sensor selection for sequential hypothesis testing

Nurali Virani, Ji Woong Lee, Shashi Phoha, Asok Ray

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

Dynamic sensor selection rules are obtained based on a context-aware measurement model in the framework of sequential hypotheses testing. The notion of context incorporates the operational conditions that directly affect sensor measurements. While a random context leads to a Bayesian decision rule, an unknown but nonrandom context yields minimax game-based rules. In either case, the resulting sensor selection rule trades off decision performance against the cost of sensor activation and the uncertainty of the true context.

Original languageEnglish (US)
Article number7040471
Pages (from-to)6889-6894
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2015-February
Issue numberFebruary
DOIs
StatePublished - Jan 1 2014
Event2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States
Duration: Dec 15 2014Dec 17 2014

Fingerprint

Sequential Testing
Context-aware
Hypothesis Testing
Sensor
Selection Rules
Sensors
Testing
Decision Rules
Minimax
Activation
Trade-offs
Chemical activation
Game
Uncertainty
Unknown
Context
Costs

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

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Dynamic context-aware sensor selection for sequential hypothesis testing. / Virani, Nurali; Lee, Ji Woong; Phoha, Shashi; Ray, Asok.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 2015-February, No. February, 7040471, 01.01.2014, p. 6889-6894.

Research output: Contribution to journalConference article

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