scholarly journals The relationship between stochastic resonance and coherence resonance in a bi-stable system

2013 ◽  
Vol 62 (7) ◽  
pp. 070501
Author(s):  
Dong Xiao-Juan ◽  
Yan Ai-Jun
2011 ◽  
Vol 279 ◽  
pp. 361-366
Author(s):  
Quan Yuan ◽  
Yan Shen ◽  
Liang Chen

Stochastic resonance (SR) is a nonlinear phenomenon which can be used to detect weak signal. The theory of SR in a biased mono-stable system driven by multiplicative and additive white noise as well as a weak periodic signal is investigated. The virtual instrument (VI) for weak signal detecting based on this theory is designed with LabVIEW. This instrument can be used to detect weak periodic signals which meets the conditions given and can greatly improved the power spectrum of the weak signal. The results that related to different sets of parameters are given and the features of these results are in accordance with the theory of mono-stable SR. Thus, the application of this theory in the detecting of weak signal is proven to be valid.


2018 ◽  
Vol 121 (8) ◽  
Author(s):  
Emanuel Mompo ◽  
Miguel Ruiz-Garcia ◽  
Manuel Carretero ◽  
Holger T. Grahn ◽  
Yaohui Zhang ◽  
...  

1992 ◽  
Vol 17 (4) ◽  
pp. 495-498
Author(s):  
Jing-Dong Bao ◽  
Yi-Zhong Zhuo ◽  
Xi-Zhen Wu

2003 ◽  
Vol 03 (01) ◽  
pp. 55-71
Author(s):  
S. C. CARMONA ◽  
M. I. FREIDLIN

Stochastic resonance effects due to arbitrarily small amplitude deterministic perturbations in dynamical systems with noise are studied. The concept of Log-Asymptotic Resonance Frequency is introduced and the relationship between its existence and some types of symmetries in the stochastic system is established; the spectrum of this kind of frequencies is determined. These symmetries are defined through the quasi-deterministic approximation of the system. The large deviation theory gives the basic machinery for this analysis.


2015 ◽  
Vol 738-739 ◽  
pp. 413-416
Author(s):  
Ji Jun Tong ◽  
Yan Qin Kang

The stochastic resonance (SR) theory provides a new idea for the detection of weak signal submerged in the strong noise. Combined with the optimization theory, this paper puts forward a stochastic resonance system based on genetic algorithm and applied it in a low concentrations gas detection. Firstly we preprocessed the input signal to satisfy the requirements of SR system, then developed the genetic algorithm to seek the maximum output signal-to-noise ratio (SNR), which was used to evaluate the performance of the system. In the end the relationship between the maximum SNR and concentration of gas was analyzed. The results of the experiments indicated the proposed method could improve the detection ability and enhance the detection limit of low gas concentrations.


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