Stochastic resonance in the FitzHugh-Nagumo system driven by bounded noise

We investigate stochastic resonance （SR） in the FitzHugh-Nagumo system under combined bounded noise and weak harmonic excitation. Taking a spectral amplification factor as a signal-to-noise ratio, we show numerically that bounded noise can induce SR by adjusting either the intensity of bounded noise or its colour. Moreover, the increase of noise colour can enhance the SR and make the peak of the SR shift toward lower noise intensities, which is more feasible in practice. Since bounded noise is flexible to model random excitation, these findings may have some potential applications in engineering, neuroscience and biology.

Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises and sampled-data

This paper is concerned with the stochastic bounded consensus tracking problems of leader-follower multi-agent systems, where the control input of an agent can only use the information measured at the sampling instants from its neighbours or the virtual leader with a time-varying reference state, and the measurements are corrupted by random noises. The probability limit theory and the algebra graph theory are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking. It is shown that the maximum allowable upper boundary of the sampling period simultaneously depends on the constant feedback gains and the network topology. Furthermore, the effects of the sampling period on the tracking performance are analysed. It turns out that from the view point of the sampling period, there is a trade-off between the tracking speed and the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.

Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with general sampling delay

In this paper we provide a unified framework for consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with a general sampling delay. First, a stochastic bounded consensus tracking protocol based on sampled data with a general sampling delay is presented by employing the delay decomposition technique. Then, necessary and sufficient conditions are derived for guaranteeing leader-follower multi-agent systems with measurement noises and a time-varying reference state to achieve mean square bounded consensus tracking. The obtained results cover no sampling delay, a small sampling delay and a large sampling delay as three special cases. Last, simulations are provided to demonstrate the effectiveness of the theoretical results.

Moment Lyapunov exponent of three-dimensional system under bounded noise excitation

In the present paper, the moment Lyapunov exponent of a codimensional two-bifurcation system is evaluted, which is on a three-dimensional central manifold and subjected to a parametric excitation by the bounded noise. Based on the theory of random dynamics, the eigenvalue problem governing the moment Lyapunov exponent is established. With a singular perturbation method, the explicit asymptotic expressions and numerical results of the second^order weak noise expansions of the moment Lyapunov are obtained in two cases. Then, the effects of the bounded noise and the parameters of the system on the moment Lyapunov exponent and the stability index are investigated. It is found that the stochastic stability of the system can be strengthened by the bounded noise.

Diffusion induced by bounded noise in a two-dimensional coupled memory system

The diffusion behavior driven by bounded noise under the influence of a coupled harmonic potential is investigated in a two-dimensional coupled-damped model. With the help of the Laplace analysis we obtain exact descriptions for a particle’s two-time dynamics which is subjected to a coupled harmonic potential and a coupled damping. The time lag is used to describe the velocity autocorrelation function and mean square displacement of the diffusing particle. The diffusion behavior for the time lag is also discussed with respect to the coupled items and the amplitude of bounded noise.

The maximal Lyapunov exponent of a co-dimension two-bifurcation system excited by a bounded noise

In the present paper, the maximal Lyapunov ex- ponent is investigated for a co-dimension two bifurcation system that is on a three-dimensional central manifold and subjected to parametric excitation by a bounded noise. By using a perturbation method, the expressions of the invari- ant measure of a one-dimensional phase diffusion process are obtained for three cases, in which different forms of the matrix B, that is included in the noise excitation term, are assumed and then, as a result, all the three kinds of singular boundaries for one-dimensional phase diffusion process are analyzed. Via Monte-Carlo simulation, we find that the an- alytical expressions of the invariant measures meet well the numerical ones. And furthermore, the P-bifurcation behav- iors are investigated for the one-dimensional phase diffusion process. Finally, for the three cases of singular botmdaries for one-dimensional phase diffusion process, analytical ex- pressions of the maximal Lyapunov exponent are presented for the stochastic bifurcation system.

Upper bound for the time derivative of entropy for a stochastic dynamical system with double singularities driven by non-Gaussian noise

A stochastic dynamical system with double singularities driven by non-Gaussian noise is investigated. The Fokker Plank equation of the system is obtained through the path-integral approach and the method of transformation. Based on the definition of Shannon＇s information entropy and the Schwartz inequality principle, the upper bound for the time derivative of entropy is calculated both in the absence and in the presence of non-equilibrium constraint. The present calculations can be used to interpret the effects of the system dissipative parameter, the system singularity strength parameter, the noise correlation time and the noise deviation parameter on the upper bound.

Stochastic bounded consensus of second-order multi-agent systems in noisy environment

This paper investigates the stochastic bounded consensus of leader-following second-order multi-agent systems in a noisy environment. It is assumed that each agent received the information of its neighbors corrupted by noises and time delays. Based on the graph theory, stochastic tools, and the Lyapunov function method, we derive the sufficient conditions under which the systems would reach stochastic bounded consensus in mean square with the protocol we designed. Finally, a numerical simulation is illustrated to check the effectiveness of the proposed algorithms.

Localization for mixed near-field and far-field sources under impulsive noise

In order to solve the problem that the performance of traditional localization methods for mixed near-field sources(NFSs)and far-field sources(FFSs)degrades under impulsive noise,a robust and novel localization method is proposed.After eliminating the impacts of impulsive noise by the weighted out-lier filter,the direction of arrivals(DOAs)of FFSs can be estimated by multiple signal classification(MUSIC)spectral peaks search.Based on the DOAs information of FFSs,the separation of mixed sources can be performed.Finally,the estimation of localizing parameters of NFSs can avoid two-dimension spectral peaks search by decomposing steering vectors.The Cramer-Rao bounds(CRB)for the unbiased estimations of DOA and range under impulsive noise have been drawn.Simulation experiments verify that the proposed method has advantages in probability of successful estimation(PSE)and root mean square error(RMSE)compared with existing localization methods.It can be concluded that the proposed method is effective and reliable in the environment with low generalized signal to noise ratio(GSNR),few snapshots,and strong impulse.

Direction finding of bistatic MIMO radar in strong impulse noise

For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.

Effects of interface bound states on the shot noise in normal metal–low-dimensional Rashba semiconductor tunnel junctions with induced s-wave pairing potential

We consider the effects of interface bound states on the electrical shot noise in tunnel junctions formed between normal metals and one-dimensional(1 D) or two-dimensional(2 D) Rashba semiconductors with proximity-induced s-wave pairing potential. We investigate how the shot noise properties vary as the interface bound state is evolved from a non-zero energy bound state to a zero-energy bound state. We show that in both 1 D and 2 D tunnel junctions, the ratio of the noise power to the charge current in the vicinity of zero bias voltage may be enhanced significantly due to the induction of the midgap interface bound state. But as the interface bound state evolves from a non-zero energy bound state to a zero-energy bound state, this ratio tends to vanish completely at zero bias voltage in 1 D tunnel junctions, while in 2 D tunnel junctions it decreases smoothly to the usual classical Schottky value for the normal state. Some other important aspects of the shot noise properties in such tunnel junctions are also clarified.

Minimax State Estimator for Uncertain Systems with L_2 Bounded Constraint

Minimax state estimation is discussed for uncerttain systems with L2 bounded constraint. A dtaity relation-equality is introduced to estimate terminal state variabes x(T) by measurable outputs . hawing a game theory, opti-mal estimation leads to a simple solution. LQL control scheme, is further discussed to make it rational in the actual application.

Chaotic motion of the dynamical system under both additive and multiplicative noise excitations

With both additive and multiplicative noise excitations, the effect on the chaotic behaviour of the dynamical system is investigated in this paper. The random Melnikov theorem with the mean-square criterion that applies to a type of dynamical systems is analysed in order to obtain the conditions for the possible occurrence of chaos. As an example, for the Duffing system, we deduce its concrete expression for the threshold of multiplicative noise amplitude for the rising of chaos, and by combining figures, we discuss the influences of the amplitude, intensity and frequency of both bounded noises on the dynamical behaviour of the Duffing system separately. Finally, numerical simulations are illustrated to verify the theoretical analysis according to the largest Lyapunov exponent and Poincaré map.

Direction of arrival estimation method based on quantum electromagnetic field optimization in the impulse noise

In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.

Robust Frequency Estimation Under Additive Mixture Noise

In many applications such as multiuser radar communications and astrophysical imaging processing,the encountered noise is usually described by the finite sum ofα-stable(1≤α<2)variables.In this paper,a new parameter estimator is developed,in the presence of this new heavy-tailed noise.Since the closed-formPDF of theα-stable variable does not exist exceptα=1 andα=2,we take the sum of the Cauchy(α=1)and Gaussian(α=2)noise as an example,namely,additive Cauchy-Gaussian(ACG)noise.The probability density function(PDF)of the mixed random variable,can be calculated by the convolution of the Cauchy’s PDF and Gaussian’s PDF.Because of the complicated integral in the PDF expression of the ACG noise,traditional estimators,e.g.,maximum likelihood,are analytically not tractable.To obtain the optimal estimates,a new robust frequency estimator is devised by employing the Metropolis-Hastings(M-H)algorithm.Meanwhile,to guarantee the fast convergence of the M-H chain,a new proposal covariance criterion is also devised,where the batch of previous samples are utilized to iteratively update the proposal covariance in each sampling process.Computer simulations are carried out to indicate the superiority of the developed scheme,when compared with several conventional estimators and the Cramér-Rao lower bound.

基于L_(2,1)范数正则化矩阵分解的图像结构化噪声平滑算法

图像去噪是数字图像处理的必要环节,对后续图像处理、分析和应用的效果有重要影响。现有基于稀疏低秩矩阵分解的图像去噪算法虽然在处理高斯、椒盐等均匀随机噪声时效果良好,但无法有效处理实际应用中可能遇到的结构化噪声问题。针对该缺陷,本文引入L_(2,1)范数将结构化噪声情形下的图像去噪问题建模为一类L_(2,1)范数正则化矩阵分解问题,并由此提出一种基于L_(2,1)范数正则化矩阵分解的图像结构化噪声平滑算法(L21NRMD)。仿真实验结果表明,在基本保持椒盐噪声去除效果的前提下,该算法可有效去除不同比例的结构化噪声,PSNR性能指标值介于69-80dB之间,差错率为0.06-0.14,较现有算法具有更好的适应性和更广的应用范围。

对等效声级Leq不小于L_(10)可能性的讨论

本文针对噪声实际监测中出现等效声级Leq大于或等于累积百分比声级L1 0 可能性的不同情况 ,通过理论与实际相结合 ,阐述了等效声级Leq大于或等于累积百分比声级L1 0

Multi-UAV cooperative target tracking with bounded noise for connectivity preservation

We investigate cooperative target tracking of multiple unmanned aerial vehicles(UAVs)with a limited communication range.This is an integration of UAV motion control,target state estimation,and network topology control.We first present the communication topology and basic notations for network connectivity,and introduce the distributed Kalman consensus filter.Then,convergence and boundedness of the estimation errors using the filter are analyzed,and potential functions are proposed for communication link maintenance and collision avoidance.By taking stable target tracking into account,a distributed potential function based UAV motion controller is discussed.Since only the estimation of the target state rather than the state itself is available for UAV motion control and UAV motion can also affect the accuracy of state estimation,it is clear that the UAV motion control and target state estimation are coupled.Finally,the stability and convergence properties of the coupled system under bounded noise are analyzed in detail and demonstrated by simulations.

Stochastic bifurcations in the SD (smooth and discontinuous) oscillator under bounded noise excitation

Stochastic bifurcations of the SD （smooth and discontinuous） oscillator with additive and/or multiplicative bounded noises are studied by the generalized cell mapping method using digraph analysis algorithm. From the global viewpoint, stochastic bifur- cation can be described as a sudden change in shape and size of a random attractor as the system parameter valies. The evolu- tionary process of stochastic bifurcation in the SD oscillator is shown in detail. Meanwhile, we show the phenomenon that un- der stochastic excitation the shape and size of random attractor and random saddle change along with the direction of unstable manifold. A plane stochastic bifurcation diagram is included.

五水平U型设计在可卷型L_(2)-偏差下的新下界

通过变换得到了五水平U型设计可卷型L_(2)-偏差的一个新表达式,基于该表达式和数学不等式得到了该偏差的一个新下界.