α稳定噪声环境下多频微弱信号检测的参数诱导随机共振现象

本文将α稳定噪声与双稳随机共振系统相结合, 研究了不同α稳定噪声环境下高低频(均为多频)微弱信号检测的参数诱导随机共振现象, 探究了α稳定噪声的特征指数α(0 < α ≤ 2)和对称参数β (-1≤ β ≤ 1)及随机共振系统参数a, b对共振输出效应的作用规律. 研究结果表明, 在不同分布的α稳定噪声环境下, 通过调节系统参数a和b均可诱导随机共振来实现多个高、低频微弱信号的检测, 且存在多个a, b参数区间均可诱导随机共振, 这些区间不随α或β的变化而变化; 在高、低频微弱信号检测中, α或β对随机共振输出效应的作用规律相同. 本研究结果将有助于α稳定噪声环境下参数诱导随机共振现象中系统参数的合理选取, 进而可为实现基于随机共振的多频微弱信号检测方法的工程应用奠定基础. 关键词： 随机共振 α稳定噪声')" href="#">α稳定噪声 多频微弱信号检测 平均信噪比增益     

Parameter-induced stochastic resonance with a periodic signal

In this paper conventional stochastic resonance (CSR) is realized by adding the noise intensity. This demonstrates that tuning the system parameters with fixed noise can make the noise play a constructive role and realize parameter-induced stochastic resonance (PSR). PSR can be interpreted as changing the intrinsic characteristic of the dynamical system to yield the cooperative effect between the stochastic-subjected nonlinear system and the external periodic force. This can be realized at any noise intensity, which greatly differs from CSR that is realized under the condition of the initial noise intensity not greater than the resonance level. Moreover, it is proved that PSR is different from the optimization of system parameters.     

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.     

A weak signal detection method based on adaptive parameter-induced tri-stable stochastic resonance

Aiming at detecting the weak signal in a strong noise background, an enhanced weak signal detection method based on adaptive parameter-induced tri-stable stochastic resonance is proposed. Firstly, because the system can switch among the monostable, bistable and tri-stable state, the potential function characteristic of tri-stable systems is studied by analyzing the potential function curves with different system parameters. And the dynamic characteristics of system parameters on the depth of the potential well is analyzed. The ranges of R and the system parameters are determined, which is essential for ensuring the system is tri-stable state. Secondly, the range of R is used as the constraint condition and the average output signal-to-noise ratio is used as the fitness function of the adaptive algorithm. The system parameters a, b, c are optimized by the differential evolution particle swarm optimization (DEPSO) method to obtain the best output effect. Finally, the proposed adaptive parameter-induced tri-stable stochastic resonance method is adopted to detect the mixed multiple high-frequency weak signal. The detection results are compared with that of adaptive bistable stochastic resonance. At the meanwhile, the method is also applied to detect the fault signal of single crystal furnace. Both the simulation analysis and experiment results show that the proposed method can effectively improve the output signal-to-noise ratio and detect multi-frequency weak signal in the strong noise background.     

Evidence of parameter-induced aperiodic stochastic resonance with fixed noise

Stochastic resonance (SR) is based on the cooperative effect between the stochastic dynamical system and the external forcing. As is well known, the cooperative effect is produced by adding noises. In this paper, we show the evidence that by changing the system parameters and the signal intensity, a nonlinear system in the presence of an input aperiodic signal can yield the cooperative effect, with the noise fixed. To quantify the nonlinear system output, we determine the theoretical bit error rate (BER). By numerical simulation, the validity of the theoretical derivation is checked. Besides, we show that parameter-induced SR is more realizable than SR via adding noises, especially when the noise intensity exceeds the resonance level, or when the characteristic of the noise is not known.     

Effects of signal spectrum varying on signal processing by parameter-induced stochastic resonance

The effects of signal spectrum varying on signal processing by the method of parameter-induced stochastic resonance (PSR) are investigated. For a binary signal with a smooth power spectral density (PSD), when the PSD curve becomes sharper and narrower, the performance of the nonlinear system via PSR is better. For a multi-frequency signal formed by sine waves with different frequencies, the larger the signal spectral density is, the lower the ability of the PSR system processing signal is. And the signal-to-noise ratio (SNR) gain of the PSR system is increased with the increasing height of the spectral line. Moreover, with the method of PSR, the stochastic signal (the combination of sine waves and noise) improvement is obvious. The results obtained via this method are superior to those with a linear filter.     

Effects of asymmetric Lévy noise in parameter-induced aperiodic stochastic resonance

We study properties of parameter-induced aperiodic stochastic resonance in the presence of asymmetric Lévy noise. The system performance is characterized by the bit error rate. Investigations are based on the numerical solution of the space-fractional Fokker-Planck equation and Monte Carlo simulations. After choosing the optimal detection threshold, it is shown that the skewness parameter β has very limited influence on the system performance. Under the same conditions, the system performance is slightly reduced with the increasing β. The stability index α has the dominant effects on the system performance. The lower value of α leads to the better system performance.     

Parameter-induced stochastic resonance in an over-damped linear system

Stochastic resonance (SR) in an over-damped linear system subjected to an excitation of bias signal modulated noise with multiplicative and additive noises is investigated. We obtain the exact expressions of the first two moments and the signal-to-noise ratio (SNR) of the output by using linear-response theory. The SNR depends non-monotonically on the intensity and the correlation time of multiplicative noise, the correlation time of additive noise, the intensity of the cross noise between multiplicative and additive noise, as well as the external field frequency. The conventional SR, the SR in a broad sense and the bona fide SR are found in the system. The influences of the asymmetries of multiplicative and additive noise, the correlation rate of the cross noise, the intensity of additive noise, the amplitude of signal and the bias on the SNR are analyzed. Moreover, we pointed out that SR can be realized by tuning the system parameter with fixed noise, i.e., parameter-induced stochastic resonance (PSR) exists.     

α稳定噪声驱动的非对称双稳随机共振现象

以微弱周期信号激励的非对称双稳系统为模型, 以信噪比增益为指标, 首先针对加性和乘性α 稳定噪声共同作用的随机共振现象展开了研究, 然后针对单独加性α 稳定噪声激励的随机共振现象进行了研究, 探究了α 稳定噪声特征指数α 和对称参数β 分别取不同值时, 系统结构参数a, b, 刻画双稳系统非对称性的偏度r以及α 稳定噪声强度放大系数Q或D对非对称双稳系统共振输出的作用规律. 研究结果表明, 无论在加性和乘性α 稳定噪声共同作用下还是在单独加性α 稳定噪声作用下, 通过调节a和b或者r均可诱导随机共振, 实现微弱信号的检测, 且有多个参数区间与之对应, 这些区间不随α 或β 的变化而变化; 在研究噪声诱导的随机共振现象时发现, 调节噪声强度放大系数也可使系统产生随机共振现象, 且达到共振状态时D的区间也不随α 或β 的变化而变化. 这些结论为α 稳定噪声环境下参数诱导随机共振中系统参数以及噪声诱导随机共振中噪声强度的合理选取提供了依据.     

The phenomenon of tristable stochastic resonance driven by $$\alpha $$-noise

In this paper, the tristable stochastic resonance (SR) phenomenon induced by \(\alpha \)-stable noise is analysed. The mechanism for realizing resonance is explored based on research concerning the potential function and resonant output of a system. The rules for resonance system parameters q, p, skewness parameter r and intensity amplification factor Q of \(\alpha \)-stable noise to act on the resonant output are explored under different values of stability index \(\alpha \) and asymmetric skewness \(\beta \) of \(\alpha \)-stable noise. The results will contribute to a reasonable selection of parameter-induced tristable SR system parameters under \(\alpha \)-stable noise, and lay the foundation for a practical engineering application of weak signal detection based on the SR.     

Stochastic resonance of a tri-stable system with α stable noise

A tri-stable system excited by weak periodic signal is taken as a model and the stochastic resonance phenomenon is investigated by additive α stable noise in this paper. The laws for the resonance system parameters q, p, skewness parameter r and intensity amplification factor Q of α stable noise to act on the resonant output are explored under different stability indicies α and asymmetric skewness β of α stable noise. The results indicate that a weak signal can be realized by tuning the system parameters q, p and r under the joint action of additive α stable noise, and the interval of q and p which can induce stochastic resonance does not change with α or β. Moreover, a certain rule is found in which adjusting the intensity amplification factor Q of α stable noise can also realize a synergistic effect when studying the noise-induced stochastic resonance, and the interval of Q does not change with α or β; the best value of the characteristic index is $\alpha =1$ under any system parameter, and the best value of the symmetry parameter is $\beta =1$ under any system parameter. So, the system performance is best when $\alpha =1$ and $\beta =1$. The results will contribute to a reasonable selection of parameter-induced stochastic resonance system parameters and noise intensity of noise-induced stochastic resonance under α stable noise.     

Analysis of weak signal detection based on tri-stable system under Levy noise

Stochastic resonance system is an effective method to extract weak signal.However,system output is directly influenced by system parameters.Aiming at this,the Levy noise is combined with a tri-stable stochastic resonance system.The average signal-to-noise ratio gain is regarded as an index to measure the stochastic resonance phenomenon.The characteristics of tri-stable stochastic resonance under Levy noise is analyzed in depth.First,the method of generating Levy noise,the effect of tri-stable system parameters on the potential function and corresponding potential force are presented in detail.Then,the effects of tri-stable system parameters w,a,b,and Levy noise intensity amplification factor D on the resonant output can be explored with different Levy noises.Finally,the tri-stable stochastic resonance system is applied to the bearing fault detection.Simulation results show that the stochastic resonance phenomenon can be induced by tuning the system parameters w,a,and b under different distributions of Levy noise,then the weak signal can be detected.The parameter intervals which can induce stochastic resonances are approximately equal.Moreover,by adjusting the intensity amplification factor D of Levy noise,the stochastic resonances can happen similarly.In bearing fault detection,the detection effect of the tri-stable stochastic resonance system is superior to the bistable stochastic resonance system.     

具有固有频率涨落的记忆阻尼线性系统的随机共振

研究了在内噪声、外噪声(固有频率涨落噪声)及周期激励信号共同作用下具有指数型记忆阻尼的广义Langevin方程的共振行为.首先将其转化为等价的三维马尔可夫线性系统,再利用Shapiro-Loginov公式和Laplace变换导出系统响应一阶矩和稳态响应振幅的解析表达式.研究发现,当系统参数满足Routh-Hurwitz稳定条件时,稳态响应振幅随周期激励信号频率、记忆阻尼及外噪声参数的变化存在"真正"随机共振、传统随机共振和广义随机共振,且随机共振随着系统记忆时间的增加而减弱.数值模拟计算结果表明系统响应功率谱与理论结果相符.     

一类线性阻尼振子的随机共振研究

针对随机有色噪声参数激励和周期调制噪声外激励联合作用下的线性阻尼振子,利用Shapiro-Loginov公式推导了系统响应的一、二阶稳态矩的解析表达式.发现这类系统存在传统的随机共振、广义的随机共振和“真正”的随机共振;当乘性噪声强度和调制噪声强度的比值大于等于1时,系统出现随机多共振现象.通过数值计算的系统响应功率谱,验证了理论分析结果. 关键词： 随机共振 周期调制的噪声 线性阻尼振子     

双稳系统随机共振的反馈控制

将双稳系统的输出反馈到输入端再作用于系统,提出了采用反馈来控制随机共振的方法.以典型双稳系统为对象,并以信噪比和功率谱放大率作为度量随机共振效应的可观察变量,分别研究了采用线性或非线性反馈函数所产生的随机共振现象.理论分析和数值仿真结果表明随机共振是可控制的.该方法特别适用于系统参数固定或难以改变的系统. 关键词： 双稳系统 随机共振 反馈控制 共振效应     

耦合双稳系统的随机共振控制

两个双稳系统经非线性耦合而成为多稳态系统,该耦合系统与单一双稳系统相比具有较高的理论研究和实际应用价值.解析地分析了耦合系统在含噪弱周期信号作用下的响应特性,给出了耦合系数和双稳系统参数对随机共振的影响,表明耦合系统的随机共振是在带状的双势阱作用下产生的,还构建了反馈耦合控制原理框图.这为在双稳类系统中人为地产生随机共振或使共振效应更加强烈即随机共振的控制及其应用提供了可靠的理论依据.数值仿真结果与理论分析完全符合. 关键词： 耦合双稳系统 随机共振 控制     

随机共振控制的频率匹配方法

根据非线性双稳系统在噪声和弱周期信号作用下产生随机共振的随机同步条件，提出了随机共振控制的频率匹配方法.理论分析和数值仿真结果表明，随机共振是可控制的，通过控制输入信号的频率和噪声的统计特性，不仅能拓宽产生随机共振的频率范围，而且能增强共振的强度，从而实现有更多的噪声能量转换为信号能量. 关键词： 随机共振 非线性双稳系统 频率匹配 控制     

Stochastic resonance in FitzHugh-Nagumo system with time-delayed feedback

The dynamics of a periodically driven FitzHugh-Nagumo system with time-delayed feedback and Gaussian white noise is investigated. The stochastic resonance which is characterized by the Fourier coefficient Q is numerically calculated. It is found that the stochastic resonance of the system is a non-monotonic function of the noise strength and the signal period. The variation of the time-delayed feedback can induce periodic stochastic resonance in the system.     

双频信号作用下耦合双稳系统的双共振特性

两个单一双稳系统经非线性耦合而成为耦合系统,将其中一个双稳系统当作参数固定的被控系统,而另一个则作为参数可调的控制系统,通过调节耦合系数和控制系统的参数能产生随机共振.给控制系统外加单一频率信号,改变其频率大小能使控制系统产生共振.由于耦合的作用,控制系统的共振将影响被控系统的随机共振,从而在耦合系统中形式双共振现象,实现了用一个共振去影响另一个共振,并能使被控系统的随机共振更加强烈.经计算机仿真证实了它的有效性. 关键词： 耦合系统 双频信号 随机共振 双共振     

基于随机共振进行弱信号探测的实验研究

非线性随机共振系统可利用噪声增强微弱信号检测的能力,为强噪声背景下微弱信号的检测开创了新方法.基于随机共振的基本原理设计了硬件电路系统,并将其应用于检测单频和多频微弱信号;通过输入模拟工程实际的带噪信号,采样所得的输出信号的频谱分析结果表明,利用随机共振技术可从强噪声背景下有效地提取出单频和多频弱信号.多频弱信号的有效提取拓展了基于随机共振原理的弱信号检测技术的应用领域,结合数字滤波处理技术有效地消除了低频噪声对信号识别的影响.基于随机共振的弱信号检测技术在信息识别与信息处理方面具有巨大的潜在的应用价值.