Open AccessFeatures extraction based on singular value decomposition and stochastic resonance
Author(s) -
Zheng An-Zong,
Yonggang Leng,
Fan Sheng-Bo
Publication year - 2012
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.61.210503
Subject(s) - stochastic resonance , singular value decomposition , signal (programming language) , noise (video) , signal transfer function , singular value , bistability , component (thermodynamics) , computer science , algorithm , physics , artificial intelligence , analog signal , telecommunications , eigenvalues and eigenvectors , quantum mechanics , image (mathematics) , programming language , transmission (telecommunications) , thermodynamics
In order to detect the weak characteristic signal submerged in heavy noise with extremely low signal-to-noise ratio, a method based on singular value decomposition (SVD) and stochastic resonance is proposed. The sampling signal is first preprocessed and reconstructed by means of SVD, and then we search for a component signal. In the component signal, the components of the characteristic signal match noise strength. Then the component signal is processed with the non-linear bistable system to obtain stochastic resonance response, thus the goal of detecting the weak characteristic signal submerged in a heavy background noise is realized.