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Award ID contains: 1717942

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  1. ; (, IEEE International Symposium on Information Theory)
    Full Text Available 
  2. ; ; (, IEEE Transactions on Information Theory)
    null (Ed.)
    Full Text Available 
  3. ; (, Proceedings of the IEEE International Symposium on Information Theory)
    Accepted Manuscript Full Text Available
  4. (, Proceedings of the International Symposium on Information Theory (ISIT))
    We propose a decentralized, sequential and adaptive hypothesis test in sensor networks, which extends Chernoff’s test to a decentralized setting. We show that the proposed test achieves the same asymptotic optimality of the original one, minimizing the expected cost required to reach a decision plus the expected cost of making a wrong decision, when the observation cost per unit time tends to zero. We also show that the proposed test is parsimonious in terms of communications. Namely, in the regime of vanishing observation cost per unit time, the expected number of channel uses required by each sensor to complete the test converges to four. 
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    Accepted Manuscript Full Text Available
  5. ; ; (, Proceedings of the IEEE International Symposium on Information Theory)
    Full Text Available 
  6. ; ; (, Proceedings of the IEEE Conference on Decision and Control (CDC))
    Accepted Manuscript Full Text Available