Effects of non-Gaussian noise on logical stochastic resonance in a triple-well potential system

In this paper, we have investigated the phenomenon of logical stochastic resonance in a trip-well potential system driven by a colored non-Gaussian noise. The effects of a non-Gaussian noise on logical stochastic resonance have been discussed, and we have found that the reliability of the logic operation is dependent on the parameter q that indicates the departure from Gaussianity. The reliable region in the parameter plane of correlation time τ and noise strength D appears and expands with the decrease of q. Furthermore, it has been found that the reliable region in the plane (q,D) expands with the increase of noise color. The phenomenon can be explained successfully by the approach of Fokker–Planck equation.     

Trichotomous noise induced stochastic resonance in a linear system

We investigate stochastic resonance in an underdamped linear system subjected to multiplicative trichotomous noise. We carry out the Shapiro?CLoginov formula to find the exact expression of output amplitude gain, and the impacts of the input signal frequency and noise parameters will be observed, such as noise switching rate or noise correlation time, noise amplitude and noise flatness. Then one can find the stochastic resonance for the proposed linear system.     

Collective stochastic resonance behavior in the globally coupled fractional oscillator

This paper investigates the exponential synchronization of chaotic Lur’e systems (CLSs) with time-varying communication delays through event-triggered sampling control. Specially, first, a discrete event-triggered sampling control scheme, which only sends necessary sampling signal through the network, is designed for CLSs. By using this controller, the number of control updates could greatly reduce. Second, by getting utmost out of the usable information on the actual sampling pattern, some new sawtooth structure terms are introduced in the constructed Lyapunov–Krasovskii functional (LKF). It is worth mentioning that, different from some existing results to restrict the LKF to be positive define on the whole sampling intervals, the LKF is positive definite only needing at sampling times thanks to the use of the new inequality in Lemma 1. Third, less conservative synchronization criteria are established and the desired control gain matrix is obtained. Finally, two Chua’s circuit numerical simulations are presented to validate the feasibility and effectiveness of the theoretical results.     

含噪双稳杜芬振子矩方程的分岔与随机共振

研究了含噪声的双稳杜芬振子矩方程的分岔与随机共振的关系，并根据它们的关系, 从另 一个角度揭示了随机共振发生的机制. 首先在It?方程的基础上，导出了双稳杜芬振子在白噪声和弱周期信号作用下的矩方程，其次以噪声强度 为分岔参数分析了矩方程的分岔特性，再次分析了矩方程的分岔与双稳杜芬振子随机共振 之间的关系，最后根据该对应关系从另一种观点提出了双稳杜芬振子随机共振的机制，该 机制是由于以噪声强度为分岔参数的矩方程发生了分岔，而分岔使得原系统响应均值的能量分布发生了转移，使能 量向频率等于输入信号频率的分量处集中，使得弱信号得到了放大，随机共振发生了.     

基于随机共振的数字闭环光纤陀螺死区现象抑制

为抑制数据闭环光纤陀螺中死区现象引致的非线性性,实验研究了随机共振效应对系统信噪比的影响。实验结果表明,以电阻热噪声作为原始噪声源,配合适当的电路设计,可获得带宽可调、零均值、正态分布的随机噪声;在陀螺闭环反馈环节中的A/D转换器前,引入相应随机噪声,利用二值量化系统的非线性性,基于随机共振效应,可以提高系统信噪比,将陀螺的死区阈值从0.37o/h降至0.15o/h。此外,对于给定的陀螺系统,噪声强度、带宽和采样频率的选择不同,抑制死区现象的效果亦不同。进一步的理论分析表明,该方法可以广泛适用于基于数字闭环结构的微弱信号检测系统。     

How synaptic plasticity affects the stochastic resonance in a modular neuronal network

Nonlinear Dynamics - This work mainly investigates how synaptic plasticity influences the stochastic resonance dynamics of delay-coupled FitzHugh–Nagumo neurons in a modular neuronal network...     

Gating function based on transmission delays and stochastic resonance in motif network with FPGA implementation

Nonlinear Dynamics - Attuned function of different brain regions relies on the precise yet flexible communication between their subsystems, and flexible gating of information flow among brain motif...     

Second-order coupled tristable stochastic resonance and its application in bearing fault detection under different noises

Bearing fault is the most likely to occur in mechanical fault, and stochastic resonance (SR), as a noise enhanced signal processing tool, can find mechanical faults as early as possible, so as to avoid larger problems. However, most of the existing research methods are based on the first-order Langevin equation. According to the previous studies of many scholars, the weak signal detection ability of the second-order system is better than that of the first-order system, and the coupled system also has better performance due to the addition of the control system. So, in order to detect the fault signal more easily, a second-order coupled tristable stochastic resonance system (SCTSR) based on the adaptive genetic algorithm (AGA) is proposed, it is an improvement on improving the first-order coupled tristable stochastic resonance system (FCTSR). First, based on the fourth-order Runge–Kutta algorithm (F-RK), the performances of monostable, bistable and tristable control systems to SCTSR are compared, it is verified that the monostable system has the best performance as SCTSR’s control system. Secondly, the equivalent potential function of SCTSR is derived, and the influences of each system parameters on it are researched. The output signal-to-noise ratio gain (SNRG) is chosen as a measure to verify that SCTSR’s performance is better than that of FCTSR, and the influences of parameters on SNRG are discussed. SCTSR and FCTSR are used to detect low-, high- and multi-frequency cosine signals combined with AGA. The simulation results are compared with the wavelet transform method, which proves the performance superiority of SR, and also prove that SCTSR is easier to detect weak signals and has a stronger de-noising ability. Finally, SCTSR and FCTSR are applied in bearing fault detection under Gaussian white noise and trichotomous noise. The results also prove that SCTSR can get larger peaks and SNRG, and it is easier to detect fault signals. This proves that SCTSR’s performance is superior that of other methods in bearing fault detection, and has better engineering application value.

     

Mixed-mode self-oscillations,stochastic excitability,and coherence resonance in flows of highly concentrated suspensions

Nonlinear Dynamics - This article presents an overview of breaking waves and liquid sloshing impact acting on rigid walls and in liquid containers. The physics of breaking waves against rigid walls...     

On simulation of a bistable system with fractional damping in the presence of stochastic coherence resonance

A bistable dynamical system with the Duffing potential, fractional damping, and random excitation has been modelled. To excite the system, we used a stochastic force defined by Wiener random process of Gaussian distribution. As expected, stochastic resonance appeared for sufficiently high noise intensity. We estimated the critical value of the noise level as a function of derivative order \(q\) . For smaller order \(q\) , damping enhancement was reported.     

The effect of fractional damping and time-delayed feedback on the stochastic resonance of asymmetric SD oscillator

Nonlinear Dynamics - This paper proposes the stiffness nonlinearities and asymmetric SD (smooth and discontinuous) oscillator under time-delayed feedback control with the fractional derivative...     

Research on parametric resonance in a stochastic van der Pol oscillator under multiple time delayed feedback control

Analytical derivations and numerical calculations are employed to gain insight into the parametric resonance of a stochastically driven van der Pol oscillator with delayed feedback. This model is the prototype of a self-excited system operating with a combination of narrow-band noise excitation and two time delayed feedback control. A slow dynamical system describing the amplitude and phase of resonance, as well as the lowest-order approximate solution of this oscillator is firstly obtained by the technique of multiple scales. Then the explicit asymptotic formula for the largest Lyapunov exponent is derived. The influences of system parameters, such as magnitude of random excitation, tuning frequency, gains of feedback and time delays, on the almost-sure stability of the steady-state trivial solution are discussed under the direction of the signal of largest Lyanupov exponent. The non-trivial steady-state solution of mean square response of this system is studied by moment method. The results reveal the phenomenon of multiple solutions and time delays induced stabilization or unstabilization, moreover, an appropriate modulation between the two time delays in feedback control may be acted as a simple and efficient switch to adjust control performance from the viewpoint of vibration control. Finally, theoretical analysis turns to a validation through numerical calculations, and good agreements can be found between the numerical results and the analytical ones.     

Using three-dimensional fractal dimension to analyze the complexity of fetal cortical surface from magnetic resonance images

This study aims to investigate the complexity of the developing fetal cortical surface based on the notion of fractal dimension (FD). Forty-four fetal MR images were selected at 22–36 weeks of gestational age (GA) and distributed between two groups: 32 normal fetal brains (excluding twins) and 12 abnormal fetal brains, including twins, mild ventricular dilatation, Cornelia de Lange syndrome (small brain), and cortical dysplasia (developmental delay). We adopted the commonly used box-counting (BC) method to estimate the FD of the developing fetal cortical surface. Results from normal fetal brains show that the increase of cortical complexity is highly correlated with fetal developing weeks of GA. In addition, after 28 weeks of GA, the value of FD increases more rapidly because of the faster development of convolved folds. In comparison with results from the normal fetal group, the abnormal fetal brains were examined and the results show that: (1) mild ventricular dilatation has no significant developing difference compared with normal fetal brains; (2) twins had lower FD than that of normal fetal brains, which may be a delay of 2–3 weeks; (3) the case of cortical dysplasia also had low FD, indicating that developing delay may mean less cortical complexity. The results of the normal group are in good agreement with fetal brain development and demonstrate the effectiveness of FD as a promising means for the quantification of complexity of the fetal cortical surface.