Signal Recovery Based on Bistable Stochastic Resonance

2008 ◽  
Author(s):  
Yong-gang Leng ◽  
Yan Guo ◽  
Ying Zhang
Keyword(s):  
Numerical Simulation ◽  
Stochastic Resonance ◽  
Bistable System ◽  
Signal Recovery ◽  
Resonance System ◽  
System Parameters ◽  
Recovery Mechanism ◽  
Pulse Distortion ◽  
Waveform Distortion ◽  
Recovery System

This paper deals with the problem of the waveform distortion in the output of a bistable stochastic resonance system. The waveform recovery formula is proposed by observing the movement track of a particle in the bistable system and the suggested recovery system. The recovery mechanism and rules with and without noise are revealed. Moreover, a novel explanation about pulse distortion caused by the particle’s transitions occurring at the wells’ inflexions is put forward. Under the stochastic influence of the noise in subthreshold stochastic resonance, we develop a method via cascaded-bistable stochastic resonance and the recovery system with tuned system parameters to restore the output waveform. The numerical simulation has presented that it can recover the waveform containing weak information submerged in noise effectively. The method is applicable to both periodic and aperiodic signals.

scholarly journals Research on Stochastic Resonance Signal’s Recovery

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Hao Wang ◽  
Jie Cao ◽  
Xiang Wei
Keyword(s):  
Stochastic Resonance ◽  
Bistable System ◽  
Signal Recovery ◽  
Weather Index ◽  
Recovery Method ◽  
Application Range ◽  
Periodic Law ◽  
Accurate Expression ◽  
Periodic Signals ◽  
System Coupling

Using stochastic resonance to detect weak periodic signals has been widely used in various fields of science, which attracts much attention of researchers due to its advantages of revealing recessive periodic laws. This paper utilized this method to seek the underlying rule of setting weather index, so we can find that how to obtain the accurate expression of original periodic law by further investigation. This paper deals with the noise-contained signal restoring on the basis of the established system coupling the inversion system and bistable system. The simulation shows that this signal recovery method inversion effect is better and the application range is wider.

scholarly journals Stochastic Resonance in a Multistable System Driven by Gaussian Noise

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Peiming Shi ◽  
Pei Li ◽  
Shujun An ◽  
Dongying Han
Keyword(s):  
Stochastic Resonance ◽  
Gaussian Noise ◽  
Noise Intensity ◽  
Signal To Noise Ratio ◽  
Gaussian White Noise ◽  
State Theory ◽  
Elimination Theory ◽  
Resonance System ◽  
System Parameters ◽  
Nonmonotonic Function

Stochastic resonance (SR) is investigated in a multistable system driven by Gaussian white noise. Using adiabatic elimination theory and three-state theory, the signal-to-noise ratio (SNR) is derived. We find the effects of the noise intensity and the resonance system parametersb,c, anddon the SNR; the results show that SNR is a nonmonotonic function of the noise intensity; therefore, a multistable SR is found in this system, and the value of the peak changes with changing the system parameters.

Mechanism of Bistable Resonance With Large Frequency

2011 ◽  
Author(s):  
Yong-gang Leng ◽  
Zhi-hui Lai ◽  
Jun-zhong Xia ◽  
Yan Guo
Keyword(s):  
Stochastic Resonance ◽  
System Structure ◽  
Bistable System ◽  
Frequency Signal ◽  
Small Frequency ◽  
System Parameters ◽  
Frequency Resonance ◽  
Large Frequency

For the response of a bistable system to a large frequency signal, the mechanism of large frequency resonance with parameter-adjusted bistable system is investigated in this work. Our research shows that the method of re-scaling frequency used in stochastic resonance does not change the bistable system structure to realize resonance at the small frequency corresponding to the large frequency, and that the method of tuning bistable system parameters can directly produce resonance at the large frequency through adjusting the system parameters to change the system structure.

Study on Heterodyne Stochastic Resonance System for Weak Signal Detection

2011 ◽  
Vol 88-89 ◽  
pp. 341-345
Author(s):  
Jun Jun Yao ◽  
Yong Mei Huang ◽  
Li Qing Hu ◽  
Min Lin
Keyword(s):  
Signal Detection ◽  
Stochastic Resonance ◽  
Frequency Measurement ◽  
Periodic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Resonance System ◽  
Resonance Theory ◽  
System Parameters ◽  
Simulation Results

The method based on stochastic resonance is a newly developed signal processing technology. Different from other methods by restraining the noise, it takes full advantage of the noises to strengthen the weak signal to improve SNR of the system. Based on stochastic resonance theory, a heterodyne system is presented in the paper to detect the frequency of the weak periodic signal. The simulation results manifest that the method is effective and the system parameters have extensive influence for frequency measurement. The parameters of the system are investigated for optimizing system design and weak signal detection.

Study on the Application of Weak Signal Recovery System Based on the Stochastic Resonance

2011 ◽  
Vol 474-476 ◽  
pp. 1033-1037 ◽  
Author(s):  
Hui Deng ◽  
Zhang Li
Keyword(s):  
Energy Transfer ◽  
Stochastic Resonance ◽  
Signal Recovery ◽  
Energy Transfer Mechanism ◽  
Weak Signal ◽  
System Behavior ◽  
Output Spectrum ◽  
Recovery Method ◽  
Recovery System ◽  
Time Waveform

Stochastic resonance (SR) enhances the nonlinear system behavior with the assistance of noise. The energy-transfer mechanism makes the weak information revealed in the output spectrum, while the time-waveform is distorted. The factors causing the deviation in the output are presented and the function of the recovery system is proposed. The numerical simulations reveal that the SR recovery method can recover the waveform containing weak information submerged in noise effectively.

Application of Generalized Stochastic Resonance to the Vibration Test

2011 ◽  
Vol 141 ◽  
pp. 21-25
Author(s):  
Ying Zhang ◽  
Shu Ming Li
Keyword(s):  
Stochastic Resonance ◽  
Input Signal ◽  
Parameter Tuning ◽  
Sampling Frequency ◽  
Bistable System ◽  
Vibration Test ◽  
System Behavior ◽  
System Parameters ◽  
Sr Method ◽  
Large Frequency

Noise, bistable system and input signal are the three essential factors in stochastic resonance (SR). The noise-induced SR method, the parameter-tuning SR method, and the twice sampling SR method change the characteristics of the noise, the bistable system and the input signal, respectively. With the new cooperation, they can all produce the SR phenomena when the system exceeds the small-parameter area. If treating the strong noise and the input signal with large frequency, the actions of the system parameters can build the system behavior in an orderly way, associated with the twice sampling frequency. The united parameter-tuning SR method adjusts the system parameters to fit the normalized frequency after the twice sampling SR, in order to make the optimal noise intensity. The application to the flow meter vibration test has presented the practicability and effectiveness of the united parameter-tuning SR method.

Image Processing Based on Tuning-Parameter Stochastic Resonance

2008 ◽  
Author(s):  
Yong-gang Leng ◽  
Yan Guo ◽  
Ying Zhang
Keyword(s):  
Image Processing ◽  
Stochastic Resonance ◽  
Processing Method ◽  
Bistable System ◽  
Tuning Parameter ◽  
Tuning Parameters ◽  
System Parameters ◽  
Image Processing Method ◽  
Output Image

Bistable stochastic resonance (BSR) can change the image signal’s histogram distribution. In this paper, the influence of bistable system parameters on the contrast of the output image is investigated through the observation of histograms. An image-processing method of BSR via tuning parameters is proposed. The experiment on the treatment of an image plus noise has proved that it can improve the quality of the image effectively.

STOCHASTIC RESONANCE ENHANCED BY WHITE NOISE IN A STOCHASTIC BISTABLE SYSTEM

2011 ◽  
Vol 25 (28) ◽  
pp. 3797-3804 ◽  
Author(s):  
GUO FENG ◽  
YU-RONG ZHOU ◽  
SHAO-FU LI
Keyword(s):  
White Noise ◽  
Stochastic Resonance ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Bistable System ◽  
Static Force ◽  
Noise Strength ◽  
Signal To Noise ◽  
System Parameters ◽  
Additive White Noise

The stochastic resonance (SR) for a stochastic bistable system driven by a static force and a periodic square-wave signal as well as by additive white noise is considered from the view of signal-to-noise ratio (SNR). It is found that the SNR appears SR behavior when it is plotted as a function of the additive noise strength or as a function of the system parameters. Moreover, the influence of the static force is opposite to that of the amplitude of the stochastic potential.

scholarly journals Parallel Array Bistable Stochastic Resonance System with Independent Input and Its Signal-to-Noise Ratio Improvement

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Wei Li ◽  
Hanzhi Lu ◽  
Yanyan Zuo
Keyword(s):  
Stochastic Resonance ◽  
Performance Improvement ◽  
Signal To Noise Ratio ◽  
Gaussian White Noise ◽  
Bistable System ◽  
Resonance System ◽  
Signal To Noise ◽  
Parallel Array ◽  
Independent Components ◽  
Noise Ratio

We study the design enhancement of the bistable stochastic resonance (SR) performance on sinusoidal signal and Gaussian white noise. The bistable system is known to show an SR property; however the performance improvement is limited. Our work presents two main contributions: first, we proposed a parallel array bistable system with independent components and averaged output; second, we give a deduction of the output signal-to-noise ratio (SNR) for this system to show the performance. Our examples show the enhancement of the system and how different parameters influence the performance of the proposed parallel array.

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