Open AccessNumerical research of twice sampling stochastic resonance for the detection of a weak signal submerged in a heavy Noise
Author(s) -
Yonggang Leng,
Tao Wang
Publication year - 2003
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.52.2432
Subject(s) - stochastic resonance , signal (programming language) , noise (video) , sampling (signal processing) , adiabatic process , detection theory , computer science , physics , statistical physics , acoustics , algorithm , telecommunications , artificial intelligence , quantum mechanics , detector , image (mathematics) , programming language
A new technique, twice sampling stochastic resonance (SR), is proposed, and with this technique, the goal of detecting a weak signal overwhelmed in a noise is r ealized under large parameters in terms of the theory of adiabatic elimination. For the purpose of practical applications, the relative parameters are investiga ted in the detection of a weak signal based on the technique. The numerical simu lation shows that the method presented here is of potential value in the signal analysis and is expected to be applied to the practically measured data processi ng in the future.