Analysis of stochastic resonance in coupled oscillator with fractional damping disturbed by polynomial dichotomous noise

Yan, Zhi; Guirao, Juan Luis García; Saeed, Tareq; Chen, Huatao; Liu, Xianbin

doi:10.1007/s11071-022-07688-w

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…[ 25 ], the cascaded SR is driven by dichotomous noise, and its internal mechanism is studied and applied to feature extraction of bearing signals. Yan et al used dichotomous noise to drive fractional SR, analyzed its internal mechanism, and derived part of the system formula [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise

Zhao

Shi

2023

Sensors

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Stochastic resonance (SR) has been widely studied as a means of signal processing since its conception. Since SR is different from other denoising methods in nature, it can be used for not only feature extraction but also signal enhancement. Additive white Gaussian noise (AWGN) is often used as a driving source in SR research due to its convenience in numerical simulation and uniform distribution, but as a special noise, it is of great significance to study the SR principle of dichotomous noise as a driving source for nonlinear dynamics. In this paper, the method of piecewise tri-stable SR (PTSR) driven by dichotomous noise is studied, and it is verified that signal enhancement can still be achieved in the PTSR system. At the same time, the influence of the parameters of the PTSR system, periodic signal, and dichotomous noise on the mean of signal-to-noise ratio gain (SNR-GM) is analyzed. Finally, dichotomous noise and AWGN are used as the driving sources of the PTSR system, and the signal enhancement ability and noise resistance ability of the two drivers are compared.

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Section: Introductionmentioning

confidence: 99%

A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise

Zhao

Shi

2023

Sensors

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“…Te improvement of potential function, the change of SR order, the adjustment of SR parameters, and the extension of SR model have been studied by many scholars [16]. Yan et al studied the behavior of particles in a fractional SR system, analyzed the frst moment of the system, and gave the steady-state conditions [17]. In reference [18], the white noise-driven neural network SR is analyzed at three levels of dynamics, and the network is composed of two modules.…”

Section: Introductionmentioning

confidence: 99%

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Zhao

Shi

2023

Security and Communication Networks

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As science advances and machines become larger and more sophisticated, it is vital to determine whether there is a mechanical failure without damaging the device. Stochastic resonance (SR), as a widely used method, can effectively extract the periodic signal in the noise and then realize the identification of mechanical faults, which is very important for safety and property protection. Most studies on SR are based on additive white Gaussian noise (AWGN) as the driving source; however, there are many kinds of noise in reality. In this paper, based on the previously proposed piecewise tri-stable SR (PTSR) model, the influence of parameters on the mean of signal-to-noise ratio gain (SNR-GM) of the system driven by Lévy noise is studied. It is also verified by simulation signals and actual signals that PTSR can also achieve feature extraction and signal enhancement with Lévy noise as the driving source, which proves that PTSR can be applied in a wider range of conditions.

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Mutual information-assisted feed-forward cascaded stochastic resonance for large parameter

Suo,

Wang,

Shen

et al. 2023

Nonlinear Dyn

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Analysis of stochastic resonance in coupled oscillator with fractional damping disturbed by polynomial dichotomous noise

Cited by 5 publications

References 44 publications

A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise

A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Mutual information-assisted feed-forward cascaded stochastic resonance for large parameter

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