The role of damping on Stochastic Resonance in a periodic potential

Saikia, Shantu

doi:10.1016/j.physa.2014.08.060

Cited by 34 publications

(15 citation statements)

References 56 publications

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“…It is clearly not a case of bifurcation at the boundary; these states have their independent identities. Bifurcations and associated chaos occur only at large F 0 values [23]. For γ ≥ .17, however, we get just one kind of trajectory whose φ and x 0 change continuously as τ is varied in the entire range (insets of Figs.…”

Section: A Pure Sinusoidal Drivementioning

confidence: 92%

Dynamical states, stochastic resonance, and ratchet effect in a biharmonically driven sinusoidal potential

Reenbohn

Mahato

2015

Phys. Rev. E

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Two stable dynamical states of trajectories of an underdamped particle, under appropriate conditions, appear naturally in a sinusoidal potential when driven by a low amplitude biharmonic external field. These states are quite stable at low temperatures but make transitions between them as the temperature is raised. The proper choice of the biharmonic drive makes it possible for the system to show, at the same time, both the phenomena of stochastic resonance and ratchet effect. Ratchet effect, in this case, a consequence of the biharmonic drive, is obtained over a large domain of parameter space. However, stochastic resonance can be obtained only over a restricted (sub)domain of parameter space and owes its existence largely to the existence of the two dynamical states.

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Section: A Pure Sinusoidal Drivementioning

confidence: 92%

Dynamical states, stochastic resonance, and ratchet effect in a biharmonically driven sinusoidal potential

Reenbohn

Mahato

2015

Phys. Rev. E

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“…At present, most of the researches on periodic potential systems are focused on the SR phenomenon. [22][23][24][25][26][27][28] Our aim is to obtain the first passage time that could be exploited to predict qualitatively the dynamic behavior, due to the presence of non-Gaussian, of periodic potential system. In general, this article is the initial study result in a periodic potential system driven by cross-correlated non-Gaussian noise and additive white noise, and to consider SR and statistical complexity problems is our further work.…”

Section: Discussionmentioning

confidence: 99%

Dynamic behavior of periodic potential system driven by cross‐correlated non‐Gaussian noise and Gaussian white noise

Guo

Lou

Dong

et al. 2021

Intl J Robust & Nonlinear

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The dynamic behavior of the periodic potential system driven by the cross-correlated non-Gaussian noise and Gaussian white noise is studied in this article. According to path integral method and unified color noise approximation, the periodic potential system is transformed into a stochastic equivalent Stratonovich stochastic differential equation. Then the Fokker-Planck equation and the expression of the steady-state probability density are derived.The fourth-order Runge-Kutta algorithm is used to calculate the 5 × 10 4 times response of the system. Meanwhile, the probability density function (PDF) of the first-passage time (FPT) is simulated, and the mean first-passage time (MFPT) is obtained by averaging these values. Finally, the influence of noise parameters on MFPT and PDF of FPT is analyzed.

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“…In fact, SR can be presented in a variety of non-linear systems. For example, the periodic potential system is one kind of typical nonlinear system [13][14][15]. Further, the method of SR in periodic system has superiority in improving the signal-to-noise ratio (SNR) [16,17].…”

Section: Introductionmentioning

confidence: 99%

Realising the decomposition of a multi‐frequency signal under the coloured noise background by the adaptive stochastic resonance in the non‐linear system with periodic potential

Huang

Zhang

et al. 2018

IET signal process.

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The authors investigate a multi-frequency signal which is decomposed failure by the traditional empirical mode decomposition (EMD) method. Moreover, the multi-frequency signal submerged in the coloured noise increases the difficulty in signal decomposition. As a result, this noisy signal is decomposed unsuccessfully by the cooperation of the adaptive stochastic resonance (SR) in the classic bistable system and EMD. Then, a method combined adaptive SR in the periodic potential system and EMD is put forward to realise the decomposition. Meanwhile, the random particle swarm optimisation algorithm is applied to reach the optimal situation when signal-to-noise ratio attains the maximum value. Different simulation results verify the effectiveness of the proposed method. The proposed method might be useful in dealing with signal processing problems.

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The role of damping on Stochastic Resonance in a periodic potential

Cited by 34 publications

References 56 publications

Dynamical states, stochastic resonance, and ratchet effect in a biharmonically driven sinusoidal potential

Dynamical states, stochastic resonance, and ratchet effect in a biharmonically driven sinusoidal potential

Dynamic behavior of periodic potential system driven by cross‐correlated non‐Gaussian noise and Gaussian white noise

Realising the decomposition of a multi‐frequency signal under the coloured noise background by the adaptive stochastic resonance in the non‐linear system with periodic potential

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