Stochastic resonance in an asymmetric tristable system driven by correlated noises

Xu, Pan; Jin, Yanfei

doi:10.1016/j.apm.2019.07.053

Cited by 59 publications

(19 citation statements)

References 39 publications

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“…e core of this method to improve optimization is that when the stochastic resonance particles do not transition, the fitness value of the individual particles in the particle swarm algorithm is evaluated according to the adopted kurtosis index, and when the stochastic resonance particles transition, the individual in the particle swarm algorithm is directly. e fitness value of the particle is assigned zero, eliminating the time-consuming process of calculating the output of the stochastic resonance system through the Runge-Kutta method and evaluating the fitness value of the particle according to the kurtosis index [20,21]. For the detection of weak pulse signals, the knowledge-based particle swarm algorithm is used to synchronously optimize the structural parameters a and b of the nonlinear bistable stochastic resonance system, and the fitness function is the kurtosis index.…”

Section: Adaptive Stochastic Resonance Process Of Weak Shock Signal Based On Knowledge-based Particle Swarm Algorithmmentioning

confidence: 99%

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Cui

Yang

Wang

et al. 2021

Security and Communication Networks

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Stochastic resonance is a new type of weak signal detection method. Compared with traditional noise suppression technology, stochastic resonance uses noise to enhance weak signal information, and there is a mechanism for the transfer of noise energy to signal energy. The purpose of this paper is to study the theory and application of weak signal detection based on stochastic resonance mechanism. This paper studies the stochastic resonance characteristics of the bistable circuit and conducts an experimental simulation of its circuit in the Multisim simulation environment. It is verified that the bistable circuit can achieve the stochastic resonance function very well, and it provides strong support for the actual production of the bistable circuit. This paper studies the stochastic resonance phenomenon of FHN neuron model and bistable model, analyzes the response of periodic signals and nonperiodic signals, verifies the effect of noise on stochastic resonance, and lays the foundation for subsequent experiments. It proposes to feedback the link and introduces a two-layer FHN neural network model to improve the weak signal detection performance under a variable noise background. The paper also proposes a multifault detection method based on the total empirical mode decomposition of sensitive intrinsic mode components with variable scale adaptive stochastic resonance. Using the weighted kurtosis index as the measurement index of the system output can not only maintain the similarity between the system output signal and the original signal but also be sensitive to impact characteristics, overcoming the missed or false detection of the traditional kurtosis index. Experimental research shows that this method has better noise suppression ability and a clear reproduction effect on details. Especially for images contaminated by strong noise (D = 500), compared with traditional restoration methods, it has better performance in subjective visual effects and signal-to-noise ratio evaluation.

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Section: Adaptive Stochastic Resonance Process Of Weak Shock Signal Based On Knowledge-based Particle Swarm Algorithmmentioning

confidence: 99%

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Cui

Yang

Wang

et al. 2021

Security and Communication Networks

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“…Though the phenomena of stochastic resonance has been seen in biological experiments and in slow environmental changes, engineering applications based on this has been a few [9][10][11][12][13][14][15] . The fundamental principle of harvesting the noise power to empower the signal or the information content of the input can prove quite useful if used for practical purposes.…”

Section: Application Of Sr In Imt Devicesmentioning

confidence: 99%

“…The main aim of this article is to demonstrate possible engineering applications of this natural phenomena, instances of which are can be found in [9][10][11] . The phenomenon of SR in a multistable system and its application in fault-diagnosis in mechanical systems has been discussed in 12,13 . Further 14 and 15 provide an extensive discussion about the use of SR in enhancement of energy harvesting in electromechanical systems.…”

mentioning

confidence: 99%

Stochastic Resonance in Insulator-Metal-Transition Systems

Bhar

Khanna

Parihar

et al. 2020

Sci Rep

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Stochastic resonance (SR) is an ingenious phenomenon observed in nature and in biological systems but has seen very few practical applications in engineering. it has been observed and analyzed in widely different natural phenomenon including in bio-organisms (e.g. Mechanoreceptor of crayfish) and in environmental sciences (e.g. the periodic occurrence of ice ages). the main idea behind SR seems quite unorthodox-it proposes that noise, that is intrinsically present in a system or is extrinsically added, can help enhance the signal power at the output, in a desired frequency range. Despite its promise and ubiquitous presence in nature, SR has not been successively harnessed in engineering applications. in this work, we demonstrate both experimentally as well as theoretically how the intrinsic threshold noise of an insulator-metal-transition (iMt) material can enable SR. We borrow inspiration from natural systems which use SR to detect and amplify low-amplitude signals, to demonstrate how a simple electrical circuit which uses an iMt device can exploit SR in engineering applications. We explore two such applications: one of them utilizes noise to correctly transmit signals corresponding to different vowel sounds akin to auditory nerves, without amplifying the amplitude of the input audio sound. this finds applications in cochlear implants where ultra-low power consumption is a primary requirement. the second application leverages the frequency response of SR, where the loss of resonance at outof-band frequencies is used. We demonstrate how to provide frequency selectivity by tuning an extrinsically added noise to the system.

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“…In fact, some scholars have verified that the influence of non-Gaussian noise in stochastic dynamics cannot be underestimated. [29][30][31][32][33] Xu and Jin 30 explored the SR and MFPT in an asymmetric tristable model driven by correlated multiplicative non-Gaussian noise and additive Gaussian white noise. And the phenomena of NES, SR as well as a double SR are found by considering the effects of correlated noises and asymmetry of potential.…”

Section: Introductionmentioning

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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Stochastic resonance in an asymmetric tristable system driven by correlated noises

Cited by 59 publications

References 39 publications

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Stochastic Resonance in Insulator-Metal-Transition Systems

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

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