@inproceedings{3c73085f6eed4bb49c0a480e6a04c0ee,
title = "A novel framework for distributed detection with dependent observations",
abstract = "In this paper, we present a unifying framework for distributed detection with dependent or independent observations. This novel framework utilizes an expanded hierarchical model by introducing a hidden variable. Facilitated by this new framework, we identify several classes of distributed detection problems with conditionally dependent observations whose optimal sensor signaling structure resembles that of the independent case. These classes of problems exhibit a decoupling effect on the form of the optimal local decision rules, much in the same way as the conditionally independent case using both the Bayesian and the Neyman-Pearson criteria.",
keywords = "Dependent observation, Distributed detection, Hierarchical independence model, Quantization",
author = "Hao Chen and Varshney, \{Pramod K.\} and Biao Chen",
year = "2010",
doi = "10.1109/ICASSP.2010.5495937",
language = "English",
isbn = "9781424442966",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3526--3529",
booktitle = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings",
address = "United States",
note = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 ; Conference date: 14-03-2010 Through 19-03-2010",
}