过阻尼谐振子的随机共振

研究了由交叉相关高斯白噪声驱动的过阻尼谐振子的随机共振,其中加法噪声被周期信号所调制,运用平稳关联函数的傅里叶变换,导出了过阻尼谐振子随机模型信噪比的精确表达式.结果揭示:在过阻尼谐振子的随机模型中存在二类随机共振.一类随机共振表现为信噪比随乘法噪声强度Q变化的曲线存在共振峰,另一类随机共振表现为信噪比随振子频率ω变化的曲线存在共振峰.大幅度改变信号频率Ω值的大小,信噪比随乘法噪声强度Q变化的曲线有单峰,一峰一谷和单调变化三种不同的形式.     

周期外力对频率涨落的过阻尼谐振子所作的功和能量随机共振

研究了周期外力对频率涨落的过阻尼谐振子系统作功的特点. 结果揭示了瞬时功率随时间的周期变化出现不对称性. 研究结果还揭示周期外力一个周期对系统所做的功随乘法噪声强度的变化出现非单调行为, 系统是否出现能量随机共振与抑制并存, 由乘法噪声与加法噪声之间互关联的符号决定. 关键词： 过阻尼谐振子 频率涨落 周期外力作功 能量随机共振与抑制     

具有周期信号调制噪声的线性模型的随机共振

研究了具有周期信号调制噪声的过阻尼线性系统的随机共振现象.当采用非对称的分段噪声 时，可以得到系统响应的一、二阶矩和信噪比的精确表达式.通过对信噪比的分析, 发现了 “真实的"随机共振和传统的随机共振现象，讨论了乘性噪声的非对称性、自相关时间和噪 声之间的相关强度对信噪比的影响. 关键词： 随机共振 信噪比 周期信号调制噪声 线性模型     

二值噪声激励下欠阻尼周期势系统的随机共振

研究了二值噪声和周期信号共同激励下欠阻尼周期势系统的随机共振. 利用随机能量法计算了系统的平均输入能量和平均输出信号的振幅和相位差, 讨论了二值噪声对随机共振的影响. 发现随着噪声强度的增大, 平均输入能量曲线存在一个极小值和一个极大值, 系统出现先抑制后共振的现象; 同时, 系统信噪比曲线随噪声强度的增加出现单峰现象, 说明系统存在随机共振现象.     

噪声交叉关联强度的时间周期调制对线性过阻尼系统的随机共振的影响

针对由加性、乘性噪声和周期信号共同作用的线性过阻尼系统, 在噪声交叉关联强度受到时间周期调制的情况下,利用随机平均法推导了系统响应的信噪比的解析表达式. 研究发现这类系统比噪声间互不相关或噪声交叉关联强度为常数的线性系统具有更丰富的动力学特性, 系统响应的信噪比随交叉关联调制频率的变化出现周期振荡型随机共振, 噪声的交叉关联参数导致随机共振现象的多样化.噪声交叉关联强度的时间周期调制的引入有利于提高对微弱周期信号检测的灵敏度和实现对周期信号的频率估计. 关键词： 随机共振 周期振荡型共振 噪声交叉关联强度 信噪比     

线性调频信号激励过阻尼双稳系统的随机共振现象研究

线性调频信号是工程中常见的一种信号, 由于其为非周期信号, 无法以频域信噪比作为衡量其是否产生随机共振的测量手段, 故鲜有文献研究以线性调频信号为激励信号的随机共振现象. 本文利用线性调频信号在最优分数阶Fourier变换域上的能量聚集性, 首次提出以最优分数阶Fourier变换域上定义的信噪比作为测量手段, 研究了线性调频信号叠加高斯白噪声激励过阻尼双稳系统的随机共振现象, 且发现了以线性调频信号为激励信号时产生的新现象, 即随着信号频率的增大, 随机共振将逐渐减弱, 并给出了合理的解释.仿真的结果与理论分析一致, 验证了本文所提出方法的有效性. 关键词： 线性调频信号 分数阶Fourier变换 随机共振     

色关联噪声驱动下双模激光随机共振

运用线性近似方法,计算得到了关联色噪声和输入周期信号作用下双模激光增益模型输出信号光强的功率密度谱和信噪比,讨论了信噪比随系统参数的变化关系.研究结果发现:在系统的参数和输入信号的频率满足一定条件时,信噪比不仅随噪声强度变化出现了传统的随机共振现象,还发现其随自饱和系数c2、输入信号频率°及交叉耦合参数b的变化都出现了随机共振.     

α稳定噪声环境下过阻尼系统中的参数诱导随机共振现象

本文采用随机模拟方法, 研究了过阻尼振子系统在α稳定噪声环境下的参数诱导随机共振现象. 结果表明, 在α噪声环境下, 调节系统参数能够诱导随机共振现象; 而且调节非线性项参数时, 随机共振效果随α稳定噪声的指数的减小而减弱, 但当调节线性项参数时, 随机共振效果则随着α稳定噪声的特征指数的减小而增强. 本文的结论在α稳定噪声环境下, 利用参数诱导随机共振原理进行弱信号检测方面具有重要的理论意义, 并有助于理解不同α稳定噪声对一般随机共振系统的共振效果的影响.     

周期调制互关联双态噪声驱动过阻尼谐振子系统的随机共振

采用统计平均法,研究了噪声间关联强度受周期信号调制的加性和乘性双态噪声驱动过阻尼谐振子系统中的随机共振现象,分析并讨论了周期调制互关联条件下互关联强度对系统随机共振的影响。研究发现在适当的噪声和信号强度下,逐步增加噪声间互关联强度,随机共振峰也经历一个非单调变化过程。     

二维势场中弹性耦合粒子的定向输运研究

建立了二维势场中弹性耦合粒子的输运模型, 其中一维上加交流驱动及噪声, 另一维上不加驱动及噪声, 分析讨论了过阻尼情形下系统和外部参量对定向流的影响. 结果表明, 粒子可以通过相互耦合使一个方向上输入的驱动能量转化到垂直方向上, 从而使无能量输入的方向产生定向流. 适当的弹簧自由长度及耦合强度可以使定向流达到极值, 特别是当耦合强度及噪声强度固定时, 定向流会随弹簧自由长度的变化而振荡, 出现多峰现象. 研究还发现, 定向流随噪声强度的变化出现随机共振现象. 当产生定向流方向上的势的不对称度达到一定程度时会出现流反转现象. 关键词： 弹性耦合 定向输运 随机共振 流反转     

Resonance phenomena in discrete systems with bichromatic input signal

We undertake a detailed numerical study of the twin phenomenon of stochastic and vibrational resonance in a discrete model system in the presence of bichromatic input signal. A two parameter cubic map is used as the model that combines the features of both bistable and threshold systems. In addition to the results already shown for continuous systems, our analysis brings out several interesting features both for vibrational and stochastic resonance, including the existence of a cross over behavior between the two. In the regime of vibrational resonance, it is shown that the additional high frequency forcing can change the effective value of the system parameter resulting in the shift of the bistable window. In the case of stochastic resonance, the study reveals a fundamental difference between the bistable and threshold mechanisms in the response, with respect to multisignal input.     

双稳系统演化的时间尺度与随机共振的加强

噪声作用下的双稳系统存在着单一势阱内的随机波动和两势阱之间的概率跃迁,这两种不同层级的运动具有不同的时间尺度,且低层级的势阱内的波动影响着高层级的势阱间的跃迁．当外作用周期信号的时间尺度与噪声诱导的势阱间概率跃迁达到随机同步时,则能产生随机共振;给系统再加第二驱动周期信号,使其时间尺度与低层级的势阱内的波动相匹配,则存在着频率吸收现象,并能增强双稳系统的随机共振效应． 关键词： 随机共振 双稳系统 层级 时间尺度     

Effect of inertia mass on the stochastic resonance driven by a multiplicative dichotomous noise

A stochastic system driven by dichotomous noise and periodic signal is investigated in the under-damped case.The exact expressions of output signal amplitude and signal-to-noise ratio(SNR) of the system are derived.Numerical results indicate that the inertial mass greatly affects the output signal amplitude and the SNR.Regardless of whether the noise is symmetric or asymmetric,the inertial mass can influence the phenomenon of stochastic resonance(SR) of the system,leading to two types of resonance phenomenon:one is coherence-resonance-like of the SNR with inertial mass,the other is the SR of the SNR with noise intensity.     

二维映射神经元模型中频率依赖的随机共振

通过数值模拟方法, 研究了在具有稳定次阈值振荡特性的二维映射神经元体系中, 噪声对体系非线性动力学的调控作用. 通过计算发现了噪声诱导的动作电位和随机共振现象. 另外,还研究了体系的控制参数及输入信号的频率对体系动力学的影响, 发现了该体系中频率依赖的随机共振现象. 关键词： 二维映射神经元模型 次阈值振荡 高斯白噪声 随机共振     

Stochastic resonance in Hopfield neural networks for transmitting binary signals

We investigate the stochastic resonance phenomenon in a discrete Hopfield neural network for transmitting binary amplitude modulated signals, wherein the binary information is represented by two stored patterns. Based on the potential energy function and the input binary signal amplitude, the observed stochastic resonance phenomena involve two general noise-improvement mechanisms. A suitable amount of added noise assists or accelerates the switch of the network state vectors to follow input binary signals more correctly, yielding a lower probability of error. Moreover, at a given added noise level, the probability of error can be further reduced by the increase of the number of neurons. When the binary signals are corrupted by external heavy-tailed noise, it is found that the Hopfield neural network with a large number of neurons can outperform the matched filter in the region of low input signal-to-noise ratios per bit.     

Stochastic resonance in hybrid scale-free neuronal networks

We study the phenomenon of stochastic resonance in a system of coupled neurons that are globally excited by a weak periodic input signal. We make the realistic assumption that the chemical and electrical synapses interact in the same neuronal network, hence constituting a hybrid network. By considering a hybrid coupling scheme embedded in the scale-free topology, we show that the electrical synapses are more efficient than chemical synapses in promoting the best correlation between the weak input signal and the response of the system. We also demonstrate that the average degree of neurons within the hybrid scale-free network significantly influences the optimal amount of noise for the occurrence of stochastic resonance, indicating that there also exists an optimal topology for the amplification of the response to the weak input signal. Lastly, we verify that the presented results are robust to variations of the system size.     

Chaos and reverse transitions in stochastic resonance

Stochastic resonance is a phenomenon that a weak signal can be amplified and optimized by the assistance of noise in bistable system. There is still not enough research on the mutual interplay among system, noise and signal. In this paper, we study the role of every parameter in nonlinear transfer and discover chaos phenomenon in stochastic resonance. To measure the influence of chaos, a trajectory decision function was proposed. Based on this function, we found two forms of stochastic resonance, clockwise resonance and counterclockwise resonance.     

Stochastic resonance and chaotic resonance in bimodal maps: A case study

We present the results of an extensive numerical study on the phenomenon of stochastic resonance in a bimodal cubic map. Both Gaussian random noise as well as deterministic chaos are used as input to drive the system between the basins. Our main result is that when two identical systems capable of stochastic resonance are coupled, the SNR of either system is enhanced at an optimum coupling strength. Our results may be relevant for the study of stochastic resonance in biological systems.