Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection

Yan Wang; Yajun Mei

doi:10.1109/ISIT.2012.6284143

Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection

Yan Wang, Yajun Mei

Global Public Health

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

Abstract

It is well known that quantization cannot increase the Kullback-Leibler divergence which can be thought of as the expected value or first moment of the log-likelihood ratio. In this paper, we investigate the quantization effects on the second moment of the log-likelihood ratio. It is shown that quantization may result in an increase in the case of the second moment, but the increase is bounded above by 2/e. The result is then applied to decentralized sequential detection problems to provide a simpler sufficient condition for asymptotic optimality theory, and the technique is also extended to investigate the quantization effects on other higher-order moments of the log-likelihood ratio and provide lower bounds on higher-order moments.

Original language	English (US)
Title of host publication	2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012
Pages	314-318
Number of pages	5
DOIs	https://doi.org/10.1109/ISIT.2012.6284143
State	Published - 2012
Event	2012 IEEE International Symposium on Information Theory, ISIT 2012 - Cambridge, MA, United States Duration: Jul 1 2012 → Jul 6 2012

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings

Other

Other	2012 IEEE International Symposium on Information Theory, ISIT 2012
Country/Territory	United States
City	Cambridge, MA
Period	7/1/12 → 7/6/12

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

Access to Document

10.1109/ISIT.2012.6284143

Cite this

Wang, Y., & Mei, Y. (2012). Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection. In 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012 (pp. 314-318). Article 6284143 (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2012.6284143

Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection. / Wang, Yan; Mei, Yajun.
2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012. 2012. p. 314-318 6284143 (IEEE International Symposium on Information Theory - Proceedings).

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

Wang, Y & Mei, Y 2012, Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection. in 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012., 6284143, IEEE International Symposium on Information Theory - Proceedings, pp. 314-318, 2012 IEEE International Symposium on Information Theory, ISIT 2012, Cambridge, MA, United States, 7/1/12. https://doi.org/10.1109/ISIT.2012.6284143

@inproceedings{042b42953a9b4fddbb8baeead1af4477,

title = "Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection",

abstract = "It is well known that quantization cannot increase the Kullback-Leibler divergence which can be thought of as the expected value or first moment of the log-likelihood ratio. In this paper, we investigate the quantization effects on the second moment of the log-likelihood ratio. It is shown that quantization may result in an increase in the case of the second moment, but the increase is bounded above by 2/e. The result is then applied to decentralized sequential detection problems to provide a simpler sufficient condition for asymptotic optimality theory, and the technique is also extended to investigate the quantization effects on other higher-order moments of the log-likelihood ratio and provide lower bounds on higher-order moments.",

author = "Yan Wang and Yajun Mei",

year = "2012",

doi = "10.1109/ISIT.2012.6284143",

language = "English (US)",

isbn = "9781467325790",

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

pages = "314--318",

booktitle = "2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012",

note = "2012 IEEE International Symposium on Information Theory, ISIT 2012 ; Conference date: 01-07-2012 Through 06-07-2012",

}

TY - GEN

T1 - Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection

AU - Wang, Yan

AU - Mei, Yajun

PY - 2012

Y1 - 2012

N2 - It is well known that quantization cannot increase the Kullback-Leibler divergence which can be thought of as the expected value or first moment of the log-likelihood ratio. In this paper, we investigate the quantization effects on the second moment of the log-likelihood ratio. It is shown that quantization may result in an increase in the case of the second moment, but the increase is bounded above by 2/e. The result is then applied to decentralized sequential detection problems to provide a simpler sufficient condition for asymptotic optimality theory, and the technique is also extended to investigate the quantization effects on other higher-order moments of the log-likelihood ratio and provide lower bounds on higher-order moments.

AB - It is well known that quantization cannot increase the Kullback-Leibler divergence which can be thought of as the expected value or first moment of the log-likelihood ratio. In this paper, we investigate the quantization effects on the second moment of the log-likelihood ratio. It is shown that quantization may result in an increase in the case of the second moment, but the increase is bounded above by 2/e. The result is then applied to decentralized sequential detection problems to provide a simpler sufficient condition for asymptotic optimality theory, and the technique is also extended to investigate the quantization effects on other higher-order moments of the log-likelihood ratio and provide lower bounds on higher-order moments.

UR - http://www.scopus.com/inward/record.url?scp=84867530857&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867530857&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2012.6284143

DO - 10.1109/ISIT.2012.6284143

M3 - Conference contribution

AN - SCOPUS:84867530857

SN - 9781467325790

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 314

EP - 318

BT - 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012

T2 - 2012 IEEE International Symposium on Information Theory, ISIT 2012

Y2 - 1 July 2012 through 6 July 2012

ER -

Quantization effect on second moment of log-likelihood ratio and its application to decentralized sequential detection

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this