@article{8c6796f7eaf84f3885761ed23a3d9948,
title = "Noise enhanced nonparametric detection",
abstract = "This paper investigates potential improvement of nonparametric detection performance via addition of noise and evaluates the performance of noise modified nonparametric detectors. Detection performance comparisons are made between the original detectors and noise modified detectors. Conditions for improvability as well as the optimum additive noise distributions of the widely used sign detector, the Wilcoxon detector, and the dead-zone limiter detector are derived. Finally, a simple and fast learning algorithm to find the optimal noise distribution solely based on received data is presented. A near-optimal solution can be found quickly based on a relatively small dataset.",
keywords = "Hypothesis testing, Noise enhanced detection, Nonparametric detection",
author = "Hao Chen and Varshney, {Pramod K.} and Steven Kay and Michels, {James H.}",
note = "Funding Information: Manuscript received November 02, 2006; revised June 24, 2008. This work was supported by AFOSR under contract FA9550-06-C-0036. Current version published February 04, 2009. The material in this paper was presented in part at the 40th Annual Conference on Information Sciences and Systems, Princeton, NJ, March 2006. H. Chen and P. K. Varshney are with the Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY 13244 USA (e-mail: hchen21@syr.edu; varshney@syr.edu). S. Kay is with Department of Electrical and Computer Engineering, University of Rhode Island, Kingston, RI 02881 USA (e-mail: kay@ele.uri.edu). J. H. Michels is with JHM Technologies, Ithaca, NY 14852 USA (e-mail: jmichels@americu.net). Communicated by L. Tong, Associate Editor for Detection and Estimation. Color versions of Figures 2–4 in this paper are available online at http://iee-explore.ieee.org. Digital Object Identifier 10.1109/TIT.2008.2009813 Copyright: Copyright 2009 Elsevier B.V., All rights reserved.",
year = "2009",
doi = "10.1109/TIT.2008.2009813",
language = "English (US)",
volume = "55",
pages = "499--506",
journal = "IEEE Transactions on Information Theory",
issn = "0018-9448",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",
}