INVESTIGATION OF STOCHASTIC RESONANCE IN MONOSTABLE SYSTEMS

2008 ◽  
Vol 18 (09) ◽  
pp. 2833-2839 ◽  
Author(s):  
N. V. AGUDOV ◽  
A. V. KRICHIGIN
Keyword(s):  
Stochastic Resonance ◽  
Output Signal ◽  
Noise Intensity ◽  
Signal To Noise Ratio ◽  
Gaussian White Noise ◽  
Periodic Signal ◽  
Signal Power ◽  
Signal To Noise ◽  
Input Noise ◽  
Power Amplification

The phenomena of stochastic resonance is studied in overdamped nonlinear monostable systems driven by a periodic signal and Gaussian white noise. It is shown that the signal power amplification as a function of input noise intensity can be different depending on nonlinearity: it can monotonically grow, decrease and it can reach a maximum at certain value of the noise intensity. Nevertheless, the output signal to noise ratio is shown to be always a decreasing function of input noise intensity.

scholarly journals Stochastic resonance in periodically driven bistable systems subjected to anomalous diffusion

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
F. Naha Nzoupe ◽  
Alain M. Dikandé
Keyword(s):  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Planck Equation ◽  
Relevant Information ◽  
Periodic Signal ◽  
Signal To Noise ◽  
Periodically Driven ◽  
Loop Area ◽  
Bistable Systems ◽  
Noise Ratio

AbstractThe occurrence of stochastic resonance in bistable systems undergoing anomalous diffusions, which arise from density-dependent fluctuations, is investigated with an emphasis on the analytical formulation of the problem as well as a possible analytical derivation of key quantifiers of stochastic resonance. The nonlinear Fokker–Planck equation describing the system dynamics, together with the corresponding Ito–Langevin equation, is formulated. In the linear response regime, analytical expressions of the spectral amplification, of the signal-to-noise ratio and of the hysteresis loop area are derived as quantifiers of stochastic resonance. These quantifiers are found to be strongly dependent on the parameters controlling the type of diffusion; in particular, the peak characterizing the signal-to-noise ratio occurs only in close ranges of parameters. Results introduce the relevant information that, taking into consideration the interactions of anomalous diffusive systems with a periodic signal, can provide a better understanding of the physics of stochastic resonance in bistable systems driven by periodic forces.

Stochastic resonance in an array of integrate-and-fire neurons with threshold

2018 ◽  
Vol 32 (16) ◽  
pp. 1850169 ◽  
Author(s):  
Bingchang Zhou ◽  
Qianqian Qi
Keyword(s):  
Stochastic Resonance ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Array Size ◽  
Periodic Signal ◽  
Signal Parameter ◽  
Input Noise ◽  
Integrate And Fire ◽  
Noisy Input ◽  
Better Than

We investigate the phenomenon of stochastic resonance (SR) in parallel integrate-and-fire neuronal arrays with threshold driven by additive noise or signal-dependent noise (SDN) and a noisy input signal. SR occurs in this system. Whether the system is subject to the additive noise or SDN, the input noise [Formula: see text] weakens the performance of SR but the array size N and signal parameter [Formula: see text] promote the performance of SR. Signal parameter [Formula: see text] promotes the performance of SR for the additive noise, but the peak values of the output signal-to-noise ratio [Formula: see text] first decrease, then increase as [Formula: see text] increases for the SDN. Moreover, when [Formula: see text] tends to infinity, for the SDN, the curve of [Formula: see text] first increases and then decreases, however, for the additive noise, the curve of [Formula: see text] increases to reach a plain. By comparing system performance with the additive noise to one with SDN, we also find that the information transmission of a periodic signal with SDN is significantly better than one with the additive noise in limited array size N.

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.

scholarly journals Application of continuous potential function stochastic resonance in early fault diagnosis of rolling bearings

2020 ◽  
Vol 53 (5-6) ◽  
pp. 767-777
Author(s):  
Xueping Ren ◽  
Jian Kang ◽  
Zhixing Li ◽  
Jianguo Wang
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
Potential Function ◽  
Output Signal ◽  
Signal To Noise Ratio ◽  
Resonance Method ◽  
Signal To Noise ◽  
Rolling Bearings ◽  
Continuous Potential ◽  
Potential Parameters

The early fault signal of rolling bearings is very weak, and when analyzed under strong background noise, the traditional signal processing method is not ideal. To extract fault characteristic information more clearly, the second-order UCPSR method is applied to the early fault diagnosis of rolling bearings. The continuous potential function itself is a continuous sinusoidal function. The particle transition is smooth and the output is better. Because of its three parameters, the potential structure is more comprehensive and has more abundant characteristics. When the periodic signal, noise and potential function are the best match, the system exhibits better denoise compared to that of other methods. This paper discusses the influence of potential parameters on the motion state of particles between potential wells in combination with the potential parameter variation diagrams discussed. Then, the formula of output signal-to-noise ratio is derived to further study the relationships among potential parameters, and then the ant colony algorithm is used to optimize potential parameters in order to obtain the optimal output signal-to-noise ratio. Finally, an early weak fault diagnosis method for bearings based on the underdamped continuous potential stochastic resonance model is proposed. Through simulation and experimental verification, the underdamped continuous potential stochastic resonance results are compared with those of the time-delayed feedback stochastic resonance method, which proves the validity of the underdamped continuous potential stochastic resonance method.

STOCHASTIC RESONANCE FOR A METAPOPULATION SYSTEM SUBJECTED TO CORRELATED COLORED NOISES

2013 ◽  
Vol 27 (18) ◽  
pp. 1350136 ◽  
Author(s):  
KANG-KANG WANG ◽  
XIAN-BIN LIU ◽  
SHENG-HONG LI
Keyword(s):  
Stochastic Resonance ◽  
Noise Intensity ◽  
Multiplicative Noise ◽  
Signal To Noise Ratio ◽  
State Theory ◽  
Descent Method ◽  
Correlated Noise ◽  
Signal To Noise ◽  
System Parameters ◽  
Fast Descent

In the present paper, for a Levins metapopulation system that is driven by correlated colored noises, the phenomenon of stochastic resonance (SR) is investigated. Based on the two-state theory and by the use of fast descent method, the expression of the signal-to-noise ratio (SNR) is obtained. Via a numerical simulation, it is shown that the conventional SR occurs in the Levins model for the different values of system parameters. And furthermore, it is revealed that, under the different conditions that if the correlation intensities between the two noises are different, i.e. positive or negative, then all the effects of the addictive noise intensity, the multiplicative noise intensity, the correlated noise intensity and the correlation time on SNR are different.

scholarly journals Stochastic Resonance in Bistable Systems: The Effect of Simultaneous Additive and Multiplicative Correlated Noises

1998 ◽  
Vol 12 (28) ◽  
pp. 1195-1202 ◽  
Author(s):  
Claudio J. Tessone ◽  
Horacio S. Wio
Keyword(s):  
Stochastic Resonance ◽  
Noise Intensity ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Bistable System ◽  
Signal To Noise ◽  
Multiplicative Noises ◽  
Bistable Systems ◽  
Resonance Response ◽  
Correlated Noises

We analyze the effect of the simultaneous presence of correlated additive and multiplicative noises on the stochastic resonance response of a modulated bistable system. We find that when the correlation parameter is also modulated, the system's response, measured through the output signal-to-noise ratio, becomes largely independent of the additive noise intensity.

scholarly journals HIGH SIGNAL-TO-NOISE RATIO GAIN BY STOCHASTIC RESONANCE IN A DOUBLE WELL

2001 ◽  
Vol 01 (03) ◽  
pp. L181-L188 ◽  
Author(s):  
ZOLTAN GINGL ◽  
PETER MAKRA ◽  
ROBERT VAJTAI
Keyword(s):  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Gaussian White Noise ◽  
Total Power ◽  
High Signal ◽  
Signal To Noise ◽  
Simulation Techniques ◽  
Response Range ◽  
Signal Simulation ◽  
Noise Ratio

We demonstrate that signal-to-noise ratio (SNR) can be significantly improved by stochastic resonance in a double well potential. The overdamped dynamical system was studied using mixed signal simulation techniques. The system was driven by wideband Gaussian white noise and a periodic pulse train with variable amplitude and duty cycle. Operating the system in the non-linear response range, we obtained SNR gains much greater than unity. In addition to the classical SNR definition, the ratio of the total power of the signal to the power of the noise part was also measured and it showed better signal improvement.

scholarly journals Asymmetric second-order stochastic resonance weak fault feature extraction method

2020 ◽  
Vol 53 (5-6) ◽  
pp. 788-795
Author(s):  
Jiachen Tang ◽  
Boqiang Shi
Keyword(s):  
Stochastic Resonance ◽  
Output Signal ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Resonance Method ◽  
Second Order ◽  
Resonance System ◽  
Signal To Noise ◽  
Weak Fault ◽  
Noise Ratio

To solve the problem that the weak fault signal is difficult to extract under strong background noise, an asymmetric second-order stochastic resonance method is proposed. By adjusting the damping factor and the asymmetry, weak signals, noise, and potential wells are matched to each other to achieve the best stochastic resonance state so that weak fault characteristics can be effectively extracted in strong background noise. Under adiabatic approximation, the effects of damping coefficient, noise intensity, and asymmetry on the output signal-to-noise ratio are discussed based on the two-state model theory. Under the same parameters, the output signal-to-noise ratio of the asymmetric second-order stochastic resonance system is better than that of the underdamped second-order stochastic resonance system. The bearing fault and field engineering experimental results are provided to justify the comparative advantage of the proposed method over the underdamped second-order stochastic resonance method.

PERIODIC AND APERIODIC STOCHASTIC RESONANCE WITH OUTPUT SIGNAL-TO-NOISE RATIO EXCEEDING THAT AT THE INPUT

1999 ◽  
Vol 09 (01) ◽  
pp. 267-272 ◽  
Author(s):  
FRANÇOIS CHAPEAU-BLONDEAU
Keyword(s):  
Nonlinear System ◽  
Stochastic Resonance ◽  
Nonlinear Effect ◽  
Output Signal ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Practical Applications ◽  
Different Types ◽  
Signal Detectability ◽  
Noise Ratio

Stochastic resonance (SR) is a nonlinear effect whereby a system is able to improve, via noise addition, the detectability of a signal in noise. SR has been demonstrated with different types of systems and signals where in each case, an appropriate detectability measure is shown improvable at the output of the stochastic resonator when noise is added at its input. A complementary issue, important for practical applications of SR, is the possibility of making the signal detectability at the ouput exceed that at the input when noise is added. We demonstrate this possibility, for both periodic and aperiodic SR, with a simple nonlinear system that we show exactly tractable analytically.

Stochastic resonance in a periodic potential system driven by cross-correlated noises and periodic signal

2019 ◽  
Vol 33 (28) ◽  
pp. 1950338
Author(s):  
Yongfeng Guo ◽  
Xiaojuan Lou ◽  
Qiang Dong ◽  
Linjie Wang
Keyword(s):  
Stochastic Resonance ◽  
Periodic Potential ◽  
Signal To Noise Ratio ◽  
Gaussian White Noise ◽  
Signal Amplitude ◽  
Periodic Signal ◽  
Gaussian Colored Noise ◽  
Potential System ◽  
Noise Cross Correlation ◽  
Correlated Noises

In this paper, the stochastic resonance (SR) in a periodic potential system driven by cross-correlated noises and periodic signal is investigated. The signal-to-noise ratio (SNR) is used to characterize the SR. Using the algorithm of fourth-order Runge–Kutta, we obtain the curves of SNR for different parameters. The effects of some system parameters, additive Gaussian white noise and multiplicative Gaussian colored noise intensity on SR are characterized by analyzing SNR curves. When increasing system parameter and noise cross-correlation strength in SNR-D, the SR of the system can be enhanced. However, the SR will be weakened by increasing other parameters. Otherwise, the phenomena in SNR-Q are opposite to in SNR-D when increasing signal amplitude and correlation time.

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