Noise enhanced nonparametric detection

Authors

Hao Chen, Syracuse University
Pramod K. Varshney, Syracuse University
Steven Kay, University of Rhode Island
James H. Michels, JHM Technologies

Document Type

Article

Date of Original Version

3-4-2009

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. © 2009 IEEE.

Publication Title, e.g., Journal

IEEE Transactions on Information Theory

Volume

55

Issue

2

Citation/Publisher Attribution

Chen, Hao, Pramod K. Varshney, Steven Kay, and James H. Michels. "Noise enhanced nonparametric detection." IEEE Transactions on Information Theory 55, 2 (2009): 499-506. doi: 10.1109/TIT.2008.2009813.