@inproceedings{c482dab82044485093ceecc2a08af1d4,
title = "Binary Recursive Estimation on Noisy Hardware",
abstract = "Recursive estimation is a basic operation in statistical inference that may be implemented and deployed on faulty hardware with error rates governed by energy consumption. We analyze the loss in estimation performance due to noise in recursive probability computation for the binary case, and develop an optimal energy allocation strategy. Simulations show the validity of analytical bounds.",
author = "Elsa Dupraz and Varshney, {Lav R.}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Symposium on Information Theory, ISIT 2019 ; Conference date: 07-07-2019 Through 12-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ISIT.2019.8849626",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "877--881",
booktitle = "2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings",
address = "United States",
}