Title
Approaching near optimal detection performance via stochastic resonance
Document Type
Conference Proceeding
Date of Original Version
12-1-2006
Abstract
This paper considers the stochastic resonance (SR) effect in the two hypotheses signal detection problem. Performance of a SR enhanced detector is derived in terms of the probability of detection PD and the probability of false alarm PFA. Furthermore, the conditions required for potential performance improvement using SR are developed. Expression for the optimal stochastic resonance noise pdf which renders the maximum PD without increasing PFA is derived. By further strengthening the conditions, this approach yields the constant false alarm rate (CFAR) receiver. Finally, detector performance comparisons are made between the optimal SR noise, Gaussian, Uniform and optimal symmetric pdf noises. © 2006 IEEE.
Publication Title, e.g., Journal
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume
3
Citation/Publisher Attribution
Chen, Hao, Pramod K. Varshney, James H. Michels, and Steven Kay. "Approaching near optimal detection performance via stochastic resonance." ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 3, (2006). doi: 10.1109/ICASSP.2006.1660645.