Binary Recursive Estimation on Noisy Hardware

Elsa Dupraz; Lav R. Varshney

doi:10.1109/ISIT.2019.8849626

Binary Recursive Estimation on Noisy Hardware

Elsa Dupraz
, Lav R. Varshney

Office of the Provost

CNRS UMR 6285

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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.

Original language	English
Title of host publication	2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	877-881
Number of pages	5
ISBN (Electronic)	9781538692912
DOIs	https://doi.org/10.1109/ISIT.2019.8849626
State	Published - Jul 2019
Event	2019 IEEE International Symposium on Information Theory, ISIT 2019 - Paris, France Duration: Jul 7 2019 → Jul 12 2019

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2019-July
ISSN (Print)	2157-8095

Conference

Conference	2019 IEEE International Symposium on Information Theory, ISIT 2019
Country/Territory	France
City	Paris
Period	07/7/19 → 07/12/19

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10.1109/ISIT.2019.8849626

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Dupraz, E., & Varshney, L. R. (2019). Binary Recursive Estimation on Noisy Hardware. In 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings (pp. 877-881). Article 8849626 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2019.8849626

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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",

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doi = "10.1109/ISIT.2019.8849626",

language = "English",

series = "IEEE International Symposium on Information Theory - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Dupraz, E & Varshney, LR 2019, Binary Recursive Estimation on Noisy Hardware. in 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings., 8849626, IEEE International Symposium on Information Theory - Proceedings, vol. 2019-July, Institute of Electrical and Electronics Engineers Inc., pp. 877-881, 2019 IEEE International Symposium on Information Theory, ISIT 2019, Paris, France, 07/7/19. https://doi.org/10.1109/ISIT.2019.8849626

Binary Recursive Estimation on Noisy Hardware. / Dupraz, Elsa; Varshney, Lav R.
2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 877-881 8849626 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Binary Recursive Estimation on Noisy Hardware

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