DocumentCode :
3407011
Title :
Scale transformation for detecting weak periodic signal of stochastic resonance
Author :
Wang, Guo-Fu ; Zhang, Hai-Ru ; Zhang, Fa-Quan ; Ye, Jin-Cai ; Wei, Li
Author_Institution :
Dept. of Inf. & Commun., Gui Lin Univ. of Electron. Technol., GuiLin, China
fYear :
2010
fDate :
22-24 Oct. 2010
Firstpage :
441
Lastpage :
444
Abstract :
Aiming at the issue of the traditional stochastic resonance only applicable to deal with low-frequency signals, a high-frequency weak signal detection method based on scale transformation is proposed in this paper. The high-frequency weak signal mixed with noise is scaled to a low frequency signal. The signal conforms to the adiabatic elimination theory. So when it acts on stochastic resonance systems, the stochastic resonance can arise. The original high frequency weak signal mixed with noise can be retrieved by scaled up by the same ratio. To deal with the unknown frequency mixed with noise, the high frequency mixed signal is scaled down continuously to achieve a suitable matching parameters for the stochastic system. According to the change of resonance spectral peak value, the unknown frequency can be found from the mixed signal. This method is effective for future application.
Keywords :
signal detection; stochastic processes; adiabatic elimination theory; high-frequency weak signal detection; low frequency signal; low-frequency signals; scale transformation; stochastic resonance systems; weak periodic signal detection; Noise; Resonant frequency; High frequency; Scale transformation; Stochastic resonance; Weak signal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Integrated Systems (ICISS), 2010 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-6834-8
Type :
conf
DOI :
10.1109/ICISS.2010.5656058
Filename :
5656058
Link To Document :
بازگشت