Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

2016 ◽  
Vol 38 ◽  
pp. 257-266 ◽  
Author(s):  
Yongfeng Guo ◽  
Yajun Shen ◽  
Jianguo Tan
Keyword(s):  
White Noise ◽  
Stochastic Resonance ◽  
Nonlinear Model ◽  
Gaussian Noise ◽  
Model Driven ◽  
Additive White Noise ◽  
Non Gaussian

CONSTRUCTIVE ACTION OF ADDITIVE NOISE IN OPTIMAL DETECTION

2005 ◽  
Vol 15 (09) ◽  
pp. 2985-2994 ◽  
Author(s):  
FRANÇOIS CHAPEAU-BLONDEAU ◽  
DAVID ROUSSEAU
Keyword(s):  
Information Processing ◽  
White Noise ◽  
Stochastic Resonance ◽  
Gaussian Noise ◽  
Additive Noise ◽  
Optimal Detection ◽  
Processing Conditions ◽  
Noise Optimization ◽  
Additive White Noise ◽  
Non Gaussian

The optimal detection of a signal of known form hidden in additive white noise is examined in the framework of stochastic resonance and noise-aided information processing. Conditions are exhibited where the performance in the optimal detection increases when the level of the additive (non-Gaussian bimodal) noise is raised. On the additive signal–noise mixture, when a threshold quantization is performed prior to the optimal detection, another form of improvement by noise can be obtained, with subthreshold signals and Gaussian noise. Optimization of the quantization threshold shows that even in symmetric detection settings, the optimal threshold can be away from the center of symmetry and in subthreshold configuration of the signals. These properties concerning non-Gaussian noise and nonlinear preprocessing in optimal detection, are meaningful to the current exploration of the various modalities and potentialities of stochastic resonance.

Virtual Instrument for Weak Signal Detecting on Monostable Stochastic Resonance

2011 ◽  
Vol 279 ◽  
pp. 361-366
Author(s):  
Quan Yuan ◽  
Yan Shen ◽  
Liang Chen
Keyword(s):  
Power Spectrum ◽  
White Noise ◽  
Stochastic Resonance ◽  
Virtual Instrument ◽  
Stable System ◽  
Periodic Signal ◽  
Nonlinear Phenomenon ◽  
Weak Signal ◽  
Additive White Noise ◽  
Periodic Signals

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.

Stochastic resonance and MFPT in an asymmetric bistable system driven by correlated multiplicative colored noise and additive white noise

2017 ◽  
Vol 31 (14) ◽  
pp. 1750113 ◽  
Author(s):  
Pei-Ming Shi ◽  
Qun Li ◽  
Dong-Ying Han
Keyword(s):  
White Noise ◽  
Stochastic Resonance ◽  
Colored Noise ◽  
First Passage Time ◽  
Passage Time ◽  
State Theory ◽  
Bistable System ◽  
Periodic Signal ◽  
Additive White Noise ◽  
Correlation Strength

This paper investigates a new asymmetric bistable model driven by correlated multiplicative colored noise and additive white noise. The mean first-passage time (MFPT) and the signal-to-noise ratio (SNR) as the indexes of evaluating the model are researched. Based on the two-state theory and the adiabatic approximation theory, the expressions of MFPT and SNR have been obtained for the asymmetric bistable system driven by a periodic signal, correlated multiplicative colored noise and additive noise. Simulation results show that it is easier to generate stochastic resonance (SR) to adjust the intensity of correlation strength [Formula: see text]. Meanwhile, the decrease of asymmetric coefficient [Formula: see text] and the increase of noise intensity are beneficial to realize the transition between the two steady states in the system. At the same time, the twice SR phenomena can be observed by adjusting additive white noise and correlation strength. The influence of asymmetry of potential function on the MFPTs in two different directions is different.

scholarly journals Stochastic resonance in FHN neural system driven by non-Gaussian noise

2012 ◽  
Vol 61 (13) ◽  
pp. 130502
Author(s):  
Zhang Jing-Jing ◽  
Jin Yan-Fei
Keyword(s):  
Stochastic Resonance ◽  
Gaussian Noise ◽  
Neural System ◽  
Non Gaussian
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