Stochastic resonance in gene transcriptional regulatory system driven by Gaussian noise and Lévy noise

Mi, Li-na; Guo, Yongfeng; Zhang, Meng; Zhuo, Xiao-Jing

doi:10.1016/j.chaos.2022.113096

Cited by 11 publications

(7 citation statements)

References 50 publications

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“…Temporarily disregarding the impact of the input signal and input noise on the system, the bistable system's approximate Langevin equation at this juncture is [16] x ′ = ax − bx 3 (8) Solving this differential equation gives an expression for the amplitude of the output x(t) of the system,…”

Section: Output Saturation Limitmentioning

confidence: 99%

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

Sun,

Qi,

Yuan

et al. 2024

Applied Sciences

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The classical bistable stochastic resonance algorithm has an inherent output saturation defect that restricts the amplitude of the output signal. This paper examines the causes of this phenomenon and its negative impact on the detection of weak signals. Proposing the Unsaturated Bistable Stochastic Resonance (UBSR) detection algorithm involves constructing a segmented potential function using a linear function to eliminate the effect of higher-order terms in the classical stochastic resonance algorithm. A new type of segmented potential function has been created by combining exponential and linear functions. This new function helps to eliminate the impact of higher-order terms in classical algorithms while also improving the noise immunity of the stochastic resonance system. This results in the development of the accelerated stochastic resonance (ASR) detection algorithm. In this paper, the Kramers escape rate and output signal-to-noise ratio of two improved stochastic resonance algorithms are theoretically derived and compared with the classical bistable stochastic resonance algorithms, and the proposed algorithms are able to effectively avoid the output saturation phenomenon and have more excellent detection performance under strong background noise.

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Section: Output Saturation Limitmentioning

confidence: 99%

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

Sun,

Qi,

Yuan

et al. 2024

Applied Sciences

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“…In the past several decades, much attention has been devoted to the research of the constructive role of noise in nonlinear dynamical systems. There are plenty of novel phenomena including stochastic resonance [1][2][3][4][5][6], noiseenhanced stability [7][8][9], synchronous enhancement [10][11][12], time-delayed feedback [13,14], noise-induced escape and mean first-passage time [15][16][17][18][19], noise-induced transport [20][21][22] and so on. Among them, the transport properties of active Brownian particles (ABP) induced by noise have been studied broadly because of declaring the origin of the self-propelled motion and potential applications in a large number of fields, such as molecular motors [23][24][25], nanoscale friction [26,27], surface smoothening [28].…”

Section: Introductionmentioning

confidence: 99%

Transport and diffusion of active Brownian particles in a new asymmetric bistable system driven by two Gaussian colored noises

Zhuo,

Guo

2024

Phys. Scr.

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The transport phenomena (drift and diffusion) of active Brownian particles in a new asymmetric bistable system with a linear bias force and a nonlinear bias force subjected to two colored noises are investigated. Two different biases break the symmetry of the potential to generate motion of the particle with a net velocity. Theoretical analysis of the system is given by virtue of the Langevin equation and the Fokker-Planck methods, which is verified by numerical simulation. The results show that: (i) coexistence of the linear bias and nonlinear bias is capable of tuning the transport of the particle, including current reversal, absolute negative mobility, directional transport; (ii) in the absence of linear bias F, the mean velocity is negative for positive nonlinear bias r but positive for negative r, that is, the nonlinear bias leads to absolute negative mobility. In the absence of nonlinear bias r, the mean velocity is positive for positive linear bias F and negative for negative F; (iii) as the absolute values of the linear bias and nonlinear bias increase, the mean velocity is promoted but the effective diffusion is suppressed; (iv) the enhancement of the multiplicative and additive noise intensities can suppress the transport and effective diffusion; and (v) the transport velocity and diffusion are facilitated with increasing the auto-correlation times of two colored noises. Furthermore, the physical mechanism for the particle’s transport is derived from the velocity distributions and the effective velocity potential gap of the above results.

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“…Qiao et al [49] approach the study of SR phenomena in alpha-stable-distributed noise by utilizing the residence-time-ratio as an evaluation index. Yonkeu and David [50] delve into the nonlinear dynamic characteristics of fractional-SR under the influence of Lévy noises, while Mi et al [51] investigate both SR and inverse SR phenomena associated with Lévy noises in genetic sequence models. He et al [52] develop a piecewise-nonlinear BSR system to examine how Lévy noise's characteristic parameters affect SR phenomena.…”

Section: Introductionmentioning

confidence: 99%

Linearly-coupled sigmoid bistable stochastic resonance for weak signal detection

Zong,

An,

Zhang

et al. 2024

Meas. Sci. Technol.

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The paper focuses on developing a stochastic resonance system designed for the detection of weak signals under Alpha-stable-distributed noises. Initially, in view of the strong impulsive characteristics of noises, a Linearly-coupled Sigmoid Bistable Stochastic Resonance (LSBSR) system is proposed, which is constructed by potential function and sigmoid function. Through formula derivation, it is theoretically proved that the output SNR of the LSBSR system is superior to that of the classical bistable stochastic resonance (CBSR) system. Then, a new signal processing strategy based on the LSBSR system is introduced. Simulation experiments have demonstrated that under the input SNR=-20dB, the detection probability of the LSBSR system exceeds 95% for the Alpha-stable-distributed noise with α=1.5. When α is reduced to 0.1, the detection probability approaches 80%, significantly outperforming other detection methods. Finally, the LSBSR system is applied to detect sea-trial signals with an SNR improvement (SNRI) of 22.5dB, which further validates the practicability of the proposed system.

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Stochastic resonance in gene transcriptional regulatory system driven by Gaussian noise and Lévy noise

Cited by 11 publications

References 50 publications

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

Transport and diffusion of active Brownian particles in a new asymmetric bistable system driven by two Gaussian colored noises

Linearly-coupled sigmoid bistable stochastic resonance for weak signal detection

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