Error exponents for decentralized detection in feedback architectures
Author(s)Tay, Wee Peng; Tsitsiklis, John N.
MetadataShow full item record
We consider the decentralized Bayesian binary hypothesis testing problem in feedback architectures, in which the fusion center broadcasts information based on the messages of some sensors to some or all sensors in the network. We show that the asymptotically optimal detection performance (as quantified by error exponents) does not benefit from the feedback messages. In addition, we determine the corresponding optimal error exponents.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Institute of Electrical and Electronics Engineers (IEEE)
Tay, Wee Peng, and John N. Tsitsiklis. Error Exponents for Decentralized Detection in Feedback Architectures. In 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2496-2499. Institute of Electrical and Electronics Engineers, 2011.
Author's final manuscript