Time delay effects of stochastic resonance induced by multiplicative periodic signal in the gene transcriptional regulatory model

Bai, Chunyan

doi:10.1016/j.physa.2018.05.025

Cited by 13 publications

(7 citation statements)

References 50 publications

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“…The research on the characteristics of SR systems is also mainly dependent on them. According to the SR system described by the model, the Fokker-Planck equation of Equation (22) can be established to analyze the effect of noise on the system. International Journal of Aerospace Engineering method is the adiabatic approximation theory.…”

Section: High-frequency Signalmentioning

confidence: 99%

“…But more signals are nonperiodic signals in practice [20]. Chow et al put forward the concept of aperiodic stochastic resonance (ASR), which makes SR from theoretical research to practical application [21][22][23][24]. In this paper, the ASR method is used to detect the weak loose particle signals covered in the noise background for the first time.…”

Section: Introductionmentioning

confidence: 99%

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Algorithm Used to Detect Weak Signals Covered by Noise in PIND

Wang

Liang

Xue

et al. 2019

International Journal of Aerospace Engineering

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Detection of the loose particles is urgently required in the spacecraft production processes. PIND (particle impact noise detection) is the most commonly used method for the detection of loose particles in the aerospace electronic components. However, when the mass of loose particles is smaller than 0.01 mg, the weak signals are difficult to be detected accurately. In this paper, the aperiodic stochastic resonance (ASR) is firstly used to detect weak signals of loose particles. The loose particle signal is simulated by the oscillation attenuation signal. The influences of structure parameters on the potential height and detection performance of ASR are studied by a numerical iteration method. The cross-correlation coefficient C 1 between input and output is chosen as a criterion for whether there is an existing a particle or not. Through normalization, the loose particle signal-labeled high frequency of 135 kHz is converted into the low-frequency band, which can be detected by the ASR method. According to the algorithm, weak signals covered by noise could be detected. The experimental results show that the detection accuracy is 66.7%. This algorithm improves the detection range of weak loose particle signals effectively.

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Section: High-frequency Signalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Algorithm Used to Detect Weak Signals Covered by Noise in PIND

Wang

Liang

Xue

et al. 2019

International Journal of Aerospace Engineering

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“…MFPT is the mean time for a system to pass from one potential well to another, which has recently garnered a lot of attention from scientific domains [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46]. It can be used to characterize the transient features of a system, assess the stability of a potential well, and reflect some particular phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Transient properties of grazing ecosystem driven by Lévy noise and Gaussian noise

Mi,

Guo,

Ding

2023

Phys. Scr.

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This paper explores how Lévy noise and Gaussian noise affect the ecological grazing system by using the fourth-order Runge-Kutta method to simulate dynamic system and the Janicki-Weron algorithm to produce Lévy noise. Two deterministic quantities, the mean first passage time (MFPT) and the probability density function (PDF) of the first passage time (FPT), are utilized to explore the transient properties of grazing ecosystem. Our research results show that: (i) The transitions between two alternative stable states can be induced by the Gaussian noise intensity, Lévy noise intensity, Lévy stability index and Lévy skewness parameter. (ii) A higher Lévy noise intensity and a larger Lévy stability index or Lévy skewness parameter make the MFPT from desert state to sustainable vegetated state shorter; a higher Gaussian noise intensity makes it longer, which indicates that increased Lévy noise intensity can mitigate ecosystem degradation; increased Gaussian noise intensity will lead to desertification of vegetation. (iii) For larger Lévy noise intensity, the MFPT from sustainable vegetated state to desert state as a function of Gaussian noise intensity exhibits one maximum value when it transformation from the sustainable vegetated state to the desert state, the noise enhanced stability (NES) phenomena of grazing ecosystems are observed.

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“…In recent decades, Stochastic Resonance (SR) [1] has been widely studied in physics, [2][3][4] biology, [5][6][7] and many other scientific fields. [8][9][10][11][12] SR is a phenomenon showing the fluctuation force acts on the system non-linearly.…”

Section: Introductionmentioning

confidence: 99%

Research and application of stochastic resonance in quad-stable potential system

He¹,

Liu²,

Zhang³

2022

Chinese Phys. B

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To solve the problem of low weak signal enhancement performance in the quad-stable system, a new Quad-stable potential Stochastic Resonance (QSR) is proposed. Firstly, under the condition of adiabatic approximation theory, the Stationary Probability Distribution (SPD), the Mean First Passage Time (MFPT), the Work (W) and the power Spectrum Amplification Factor (SAF) are derived, and the impacts of system parameters on them are also deeply analyzed. Secondly, numerical simulations are performed to compare QSR with the Classical Tri-stable Stochastic Resonance (CTSR) by using the Genetic Algorithm (GA) and the fourth-order Runge-Kutta algorithm. It shows that the Signal-to-Noise Ratio (SNR) and Mean Signal-to-Noise Increase (MSNRI) of QSR are higher than CTSR, which indicates that QSR has superior noise immunity than CTSR. Finally, the two systems are applied in the detection on real bearing faults. The experimental results show that QSR is superior to CTSR, which provides a better theoretical significance and reference value for practical engineering application.

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Time delay effects of stochastic resonance induced by multiplicative periodic signal in the gene transcriptional regulatory model

Cited by 13 publications

References 50 publications

Algorithm Used to Detect Weak Signals Covered by Noise in PIND

Algorithm Used to Detect Weak Signals Covered by Noise in PIND

Transient properties of grazing ecosystem driven by Lévy noise and Gaussian noise

Research and application of stochastic resonance in quad-stable potential system

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