Average consensus of multi-agent systems with communication time delays and noisy links

In this paper,we consider the average-consensus problem with communication time delays and noisy links.We analyze two different cases of coupling topologies:fixed and switching topologies.By utilizing the stability theory of the stochastic differential equations,we analytically show that the average consensus could be achieved almost surely with the perturbation of noise and the communication time delays even if the time delay is time-varying.The theoretical results show that multi-agent systems can tolerate relatively large time delays if the noise is weak,and they can tolerate relatively strong noise if the time delays are low.The simulation results show that systems with strong noise intensities yield slow convergence.     

Consensus in noisy environments with switching topology and time-varying delays

In this paper, the leader-following consensus problem of noise perturbed multi-agent systems with time-varying delays is investigated. We analyze two different cases of coupling topologies: fixed topology and switching topology. Based on the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, it is analytically proved that the consensus could be achieved almost surely with the perturbation of noise and communication time delays. Furthermore, numerical examples are provided to illustrate the effectiveness of the theoretical results. The simulation results show that the speed of convergence in environments with relatively strong noise intensity is lower than that in environments with relatively weak noise intensity.     

Synchronization of noise-perturbed optical systems with multiple time delays

In this paper, complete synchronization and generalized synchronization between two unidirectionally coupled optical systems with multiple time delays and noise perturbation are investigated. Sufficient conditions for both complete synchronization and generalized synchronization are rigorously established. Numerical simulations fully support the theoretical results. The effect of parameter mismatch on the quality of synchronization is also explored.     

Impact of modulated multiple optical feedback time delays on laser diode chaos synchronization

By studying laser diodes subject to multiple time-delayed optical feedback, we demonstrate that the signatures of time delays in the autocorrelation function of the laser output can be erased in systems incorporating modulated feedback time delays. This property enhances the suitability of such laser systems highly suitable for secure chaos-based communication systems. Chaos synchronization properties of a laser-based modulated multiple time-delayed system are also reported for the first time.     

Adaptive lag synchronization in unknown stochastic chaotic neural networks with discrete and distributed time-varying delays

In this Letter, we have dealt with the problem of lag synchronization and parameter identification for a class of chaotic neural networks with stochastic perturbation, which involve both the discrete and distributed time-varying delays. By the adaptive feedback technique, several sufficient conditions have been derived to ensure the synchronization of stochastic chaotic neural networks. Moreover, all the connection weight matrices can be estimated while the lag synchronization is achieved in mean square at the same time. The corresponding simulation results are given to show the effectiveness of the proposed method.     

Associated relaxation time and intensity correlation function of a bistable system driven by cross-correlation additive and multiplicative coloured noise sources

The associated relaxation time and the intensity correlation function of a bistable system driven by an additive and a multiplicative coloured noise with coloured cross-correlation are investigated. Using the Novikov theorem and the projection operator method, the analytic expressions of the stationary probability distribution P_st(x), the relaxation time T_c, and the normalized correlation function C(s) of the system are obtained. The effects of the noise intensity, the cross-correlation strength λ and the cross-correlation time τ are discussed. By numerical computation, it is found that the cross-correlation strength |λ| and the quantum noise intensity D decrease the relaxation of the system from unstable points. The cross-correlation time τ delays relaxation of the system from unstable points. The cross-correlation strength λ and the cross-correlation time τ can alter the effects of the pump noise intensity Q. Thus, the relaxation time T_c is a stochastic resonant phenomenon, and distribution curves exhibit a single-maximum structure.     

Exponential synchronization of stochastic neural networks with leakage delay and reaction-diffusion terms via periodically intermittent control

We explore the issue of integrating leakage delay, stochastic noise perturbation, and reaction-diffusion effects into the study of synchronization for neural networks with time-varying delays. By using Lyapunov stability theory and stochastic analysis approaches, a periodically intermittent controller is proposed to guarantee the exponential synchronization of proposed coupled neural networks based on p-norm. Some existing results are improved and extended. The usefulness and superiority of our theoretical results are illustrated by a numerical example.     

三光子吸收效应与误码率

本文用噪音微扰场讨论了三光子吸收效应对光纤放大器的增益噪音和误码率的影响.由此得到三光子吸收效应能抑制该类噪音和减小误码率而有利于光孤子通信的结论.     

非一致通信时滞动力学网络上的接连滞后同步

在动力学网络中,节点与节点之间的通信通常存在时滞,并且不同节点之间的通信时滞往往是不同的(即非一致通信时滞),研究非一致通信时滞动力学网络上的接连滞后同步,更具现实意义.为此,本文首先构建含有非一致通信时滞的动力学网络模型.其次分别设计线性反馈控制和自适应反馈控制,利用Lyapunov函数方法,重点分析了该网络的接连滞后同步的稳定性,得到了同步稳定的充分条件.最后,选取蔡氏电路作为局部动力学,又分别选取了链式网络和星型网络这两种拓扑结构来验证理论结果的正确性和有效性.     

增益噪声对光孤子通信系统码率距离积的限制

在采用周期性能量补偿的全光孤子通讯系统中,比特率距离积受到孤子脉冲到达时间的Gordon-Haus效应的限制。本文讨论有损光纤中微扰对孤子群速度偏移的影响,分析集中式和分布式能量补偿方式下,增益噪声引起的孤子到达时间抖动,并由此得出系统的极限比特率距离积的大小。分析结果表明:在实际系统中,分布式能量补偿方式下系统极限比特率距离积一般要比集中式能量补偿方式下的高出一倍以上。 关键词：     

Stochastic impact in Fitzhugh–Nagumo neural system with time delays driven by colored noises

In this paper, stochastic behavior of FitzHugh–Nagumo neural system with two different kinds of time delays driven by colored noises is investigated. Based on the extended unified colored noise theory and the method of the probability density approximation, the Fokker–Planck equation and the steady-state probability density function are derived. Then through the two-state theory, the analytical expression of the signal-to-noise ratio (SNR) is also obtained. Finally, the effects of time delays and noise auto-correlation times in nonlinear dynamical system on the stationary probability density and the SNR are discussed respectively.     

Influence of strong noise on the decline and propagation of population in the delayed Malthus-Verhulst model

The effects of strong noise on the decline and propagation processes of a population in the Malthus-Verhulst model with time delay are investigated by a stochastic simulation. Time delays in two different processes are concurrent in ecosystems. The simulation results indicate that: The stability of the population is enhanced by the decreasing multiplicative noise intensity and the increasing delay time. The replacement of old individuals with young ones is accelerated by an increasing multiplicative noise intensity, an increasing additive noise intensity and a decreasing delay time. An increasing multiplicative noise intensity will drive the population of species to fluctuate more largely.     

Gibbs sampling for time-delay-and amplitude estimation in underwater acoustics

Multipath arrivals at a receiving sensor are frequently encountered in many signal-processing areas, including sonar, radar, and communication problems. In underwater acoustics, numerous approaches to source localization, geoacoustic inversion, and tomography rely on accurate multipath arrival extraction. A novel method for estimation of time delays and amplitudes of arrivals with maximum a posteriori (MAP) estimation is presented here. MAP estimation is optimal if appropriate statistical models are selected for the data; implementation, requiring maximization of a multidimensional function, is computationally demanding. Gibbs sampling is proposed as an efficient means for estimating necessary posterior probability distributions, bypassing analytical calculations. The Gibbs sampler includes as unknowns time delays, amplitudes, noise variance, and number of arrivals. Through Monte Carlo simulations, the method is shown to have a performance very close to that of analytical MAP estimation. The method is also shown to be superior to expectation-maximization, which is often applied to time-delay estimation. The Gibbs sampling approach is demonstrated to be more informative than other time-delay estimation methods, providing complete posterior distributions compared to just point estimates; the distributions capture the uncertainty in the problem, presenting likely values of the unknowns that are different from simple point estimates.     

Symbolic dynamics and synchronization of coupled map networks with multiple delays

We use symbolic dynamics to study discrete-time dynamical systems with multiple time delays. We exploit the concept of avoiding sets, which arise from specific non-generating partitions of the phase space and restrict the occurrence of certain symbol sequences related to the characteristics of the dynamics. In particular, we show that the resulting forbidden sequences are closely related to the time delays in the system. We present two applications to coupled map lattices, namely (1) detecting synchronization and (2) determining unknown values of the transmission delays in networks with possibly directed and weighted connections and measurement noise. The method is applicable to multi-dimensional as well as set-valued maps, and to networks with time-varying delays and connection structure.     

Recovery of delay time from time series based on the nearest neighbor method

We propose a method for the recovery of delay time from time series of time-delay systems. The method is based on the nearest neighbor analysis. The method allows one to reconstruct delays in various classes of time-delay systems including systems of high order, systems with several coexisting delays, and nonscalar time-delay systems. It can be applied to time series heavily corrupted by additive and dynamical noise.     

Stationary response of multi-degree-of-freedom vibro-impact systems to Poisson white noises

The stationary response of multi-degree-of-freedom (MDOF) vibro-impact (VI) systems to random pulse trains is studied. The system is formulated as a stochastically excited and dissipated Hamiltonian system. The constraints are modeled as non-linear springs according to the Hertz contact law. The random pulse trains are modeled as Poisson white noises. The approximate stationary probability density function (PDF) for the response of MDOF dissipated Hamiltonian systems to Poisson white noises is obtained by solving the fourth-order generalized Fokker-Planck-Kolmogorov (FPK) equation using perturbation approach. As examples, two-degree-of-freedom (2DOF) VI systems under external and parametric Poisson white noise excitations, respectively, are investigated. The validity of the proposed approach is confirmed by using the results obtained from Monte Carlo simulation. It is shown that the non-Gaussian behaviour depends on the product of the mean arrival rate of the impulses and the relaxation time of the oscillator.     

Soliton optical phase control by use of in-line filters

We address the problem of soliton phase jitter caused by fiber amplifier noise in a communication channel. An analytical expression for phase jitter is derived by use of perturbation theory. In the absence of filters the variance of the phase is found to be proportional to the cube of the propagation distance, but it increases only linearly if in-line filters are used. We verify with simulations that in-line filters maintain the phase jitter at a level that is tolerable for transoceanic links.     

具有不同时延的多智能体系统一致性分析

针对有向加权且存在全局可达点的静态网络拓扑, 考虑了同时具有通信时延和输入时延的一阶、二阶智能体系统的运动一致性问题. 基于广义Nyquist准则与频域控制理论的方法, 分析并得到了网络中所有智能体渐进收敛到一致状态的充分条件. 通过该条件发现一致性的达到只与系统的耦合强度、智能体的输入时延以及各自的连接状态信息有关, 与通信时延无关. 但是, 通信时延的存在却要影响系统的动态特性. 仿真实验结果进一步验证了理论分析所得结论的正确性.     

Source-filter Comparison of Measurements of Fundamental Frequency Perturbation and Amplitude Perturbation for Synthesized Voice Signals

SUMMARY: An investigation of the effect of glottal source aperiodicities (jitter, shimmer, and aspiration noise) on the estimation of fundamental frequency (f0) perturbation and amplitude perturbation, of synthesized, glottal source and voiced speech waveforms, is considered. Firstly, 4, cycle-event f0 estimators are examined: (1) waveform matching of the low-pass filtered waveform, (2) positive peaks (PPs) from the speech waveform, (3) PPs from the low-pass filtered waveform, and (4) positive zero crossings from the low-pass filtered waveform. The analysis shows that f0 perturbation measures taken from the low-pass filtered waveform are affected by both amplitude perturbation and random glottal noise, whereas, f0 perturbation measures taken from the PPs of the original waveform are affected by noise but not by amplitude perturbation. It is shown for the low-pass filter methods that the effects of amplitude perturbation and noise lead to increased errors in the measurement of f0 perturbation for the synthesized speech waveforms when compared with the synthesized glottal waveforms. Shimmer of the synthesized speech waveform is approximately equal to shimmer of the synthesized glottal source. However, noise and jitter affect measures of amplitude perturbation. The estimation of f0 perturbation from the synthesized speech waveform is shown to be nonlinearly related to f0 perturbation estimation from the synthesized glottal waveform as a consequence of the filtering action of the vocal tract. Low-pass filtering the voiced speech waveform is shown to provide a partial solution to this problem.