Gaussian Mixture Noise Improving Nonlinear Multiple Signal Detection

DOI

10.2991/icacsei.2013.7How to use a DOI?

Keywords

Multiple signal detection, probability of detection error, Gaussian mixture noise, stochastic resonance.

Abstract

Based on a nonlinear signal detector, stochastic resonance (SR) of noise-improved multiple signal detection is discussed for Gaussian mixture noise with different parameters. Signal transits from supra-threshold to sub-threshold when the threshold of the nonlinear signal detector is raised and noise transits from unimodal to bimodal when the parameter in Gaussian mixture noise increases, the occurrence of SR is studied in detail. The evolution of SR is a gradual process, which isn't affected completely by whether the signal is supra-threshold or sub-threshold, or by whether the noise is unimodal or bimodal. Based on computer simulation, for different fixed noise parameters and detector thresholds, the existence of SR shows a variety of circumstances and the detection efficacy can be improved rapidly when the sample number increases. These results show that the occurrence of SR depends strongly on the parameter in Gaussian mixture noise, the threshold of the nonlinear multiple signal detector and the sample number, and is their complex synergy.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - You guo Wang
AU  - Huan Li
AU  - Qiu yun Hu
PY  - 2013/08
DA  - 2013/08
TI  - Gaussian Mixture Noise Improving Nonlinear Multiple Signal Detection
BT  - Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)
PB  - Atlantis Press
SP  - 23
EP  - 29
SN  - 1951-6851
UR  - https://doi.org/10.2991/icacsei.2013.7
DO  - 10.2991/icacsei.2013.7
ID  - Wang2013/08
ER  -