二端梯形网络等效复阻抗的普适研究

对二端梯形网络等效复阻抗进行了研究,通过网络分析构建非线性差分方程模型,给出了梯形网络等效复阻抗的普适规律,同时分别对LC网络与非理想传输线等情形进行了具体研究,并与相关结果进行了比较.     

Behaviours in a dynamical model of traffic assignment with elastic demand

This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.     

不平衡电桥的网络分析

基于A参数，利用网络分析法导出了不平衡电桥的输入、输出电阻和输出电流表达式，同时给出了电桥灵敏度的表达式，并将结果与相关讨论进行了比较。     

一种具有正弦基函数权值的反馈型神经网络模型

提出了一种新的两层反馈型神经网络模型. 该网络采用正弦基函数作为权值, 神经元激活函数为线性函数, 连接形式为两层反馈型结构. 研究并定义了该反馈型神经网络的能量函数, 分析了网络运行的稳定性问题, 并证明了在Liapunov意义下网络运行的稳定性. 网络运行过程中, 其权值不做调整(但随时间按正弦规律变化), 网络状态不断地转换. 随着网络状态变化其能量不断减小, 最终在达到稳定时能量到达极小点. 由于该反馈型神经网络权值为正弦函数, 特别适合于周期信号的自适应逼近和检测, 为实际中周期性信号检测与处理提供了一种新的、有效的网络模型和方法. 作为应用实例把该网络应用于电力系统中电压凹陷特征量实时检测, 仿真结果表明, 网络用于信号检测不仅有很高的静态精度, 而且有非常好的动态响应特性.     

基于神经网络的托卡马克能量约束时间预测

使用机器学习理论中的神经网络方法,根据通用逼近原理对能量约束时间的复杂函数进行逼近,采用托卡马克装置的典型实验数据,设计一种组合结构的神经网络。通过大量的调参试验,给出一套性能最好的参数组合,并与传统幂指数形式的多元线性回归方法进行准确性和数据集迁移能力的比较。结果表明：神经网络模型对于能量约束时间的预测准确率更高,回归性能更好,且具有一定的抗噪声能力,更适合作为能量约束时间的定标或预测工具。     

States and transitions in mixed networks

A network is named as mixed network if it is composed of N nodes, the dynamics of some nodes are periodic, while the others are chaotic. The mixed network with all-to-all coupling and its correspond- ing networks after the nonlinearity gap-condition pruning are investigated. Several synchronization states are demonstrated in both systems, and a first-order phase transition is proposed. The mixture of dynamics implies any kind of synchronous dynamics for the whole network, and the inixed networks may be controlled by the nonlinearity gap-condition pruning.     

The noise factor of receiver coil matching networks in MRI

In typical MRI applications the dominant noise sources in the received signal are the sample, the coil loop and the preamplifier. We hypothesize that in some cases (e.g. for very small receiver coils) the matching network noise has to be considered explicitly. Considering the difficulties of direct experimental determinations of the noise factor of matching networks with sufficient accuracy, it is helpful to estimate the noise factor by calculation. A useful formula of the coil matching network is obtained by separating commonly used coil matching network into different stages and calculating their noise factor analytically by a combination of the noise from these stages. A useful formula of the coil matching network is obtained. ADS simulations are performed to verify the theoretical predictions. Thereafter carefully-designed proof-of-concept phantom experiments are carried out to qualitatively confirm the predicted SNR behavior. The matching network noise behavior is further theoretically investigated for a variety of scenarios. It is found that in practice the coil matching network noise can be improved by adjusting the coil open port resonant frequency.     

模糊对向传播网络数据融合目标识别方法

重点研究了模糊对向传播网络 (FCPN)模型。针对数据融合和目标识别的特点 ,提出了基于模糊对向传播网络的融合目标识别方法和改进的模糊对向传播网络 (MFCPN)融合结构。利用仿真数据对网络的训练算法和融合结构进行了实验研究。结果表明 ,模糊对向传播网络较误差后向传播网络 (BPN)能够有效地实现融合识别 ;改进的模糊对向传播网络融合结构是可行的。同时还对FCPN和MFCPN应用于前视红外 (FLIR)和可见光摄像机目标跟踪系统进行了应用研究。     

基于强制进化随机游走算法的质量交换网络综合

针对现有质量交换网络优化方法存在的不足, 提出一种适用于质量交换网络综合的强制进化随机游走算法。通过随机增大或减小质量交换器的传质负荷、分流比以及贫流股的流量, 并设置最小阈值实现网络连续和整型变量的同步优化; 通过以较小概率接受差解, 增强结构变异, 使算法更好地兼顾质量交换网络的全局和局部搜索。在2个质量交换网络实例中的应用表明, 优化结果优于文献最优结果, 算法保持了个体的独立进化且具有良好的全局和局部搜索能力。     

复杂网络上灾害蔓延动力学研究

针对关键生命线系统，如电网、供水网、供气网、交通网、通信网等的一些共性特征，建立一个普适性的灾害蔓延动力学模型. 这个模型考虑网络结点的自修复功能、灾害蔓延机制和内部随机噪声，并研究自修复因子、延迟时间因子和噪声强度三个重要特征参数对三种网络(随机网络、无标度网络和小世界网络)结点修复率和崩溃结点数的影响. 模拟结果与这些实际生命线系统的特征一致，表明所建立的模型可以有效地模拟生命线系统的灾害演化动力学. 关键词： 复杂网络 生命线系统 灾害蔓延     

Disturbance rejection and H∞ pinning control of linear complex dynamical networks

This paper concerns the disturbance rejection problem of a linear complex dynamical network subject to external disturbances.A dynamical network is said to be robust to disturbance,if the H ∞ norm of its transfer function matrix from the disturbance to the performance variable is satisfactorily small.It is shown that the disturbance rejection problem of a dynamical network can be solved by analysing the H ∞ control problem of a set of independent systems whose dimensions are equal to that of a single node.A counter-intuitive result is that the disturbance rejection level of the whole network with a diffusive coupling will never be better than that of an isolated node.To improve this,local feedback injections are applied to a small fraction of the nodes in the network.Some criteria for possible performance improvement are derived in terms of linear matrix inequalities.It is further demonstrated via a simulation example that one can indeed improve the disturbance rejection level of the network by pinning the nodes with higher degrees than pinning those with lower degrees.     

Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks

Increasing demand in the backbone Dense Wavelength Division (DWDM) Multiplexing network traffic prompts an introduction of new solutions that allow increasing the transmission speed without significant increase of the service cost. In order to achieve this objective simpler and faster, DWDM network reconfiguration procedures are needed. A key problem that is intrinsically related to network reconfiguration is that of the quality of transmission assessment. Thus, in this contribution a Machine Learning (ML) based method for an assessment of the quality of transmission is proposed. The proposed ML methods use a database, which was created only on the basis of information that is available to a DWDM network operator via the DWDM network control plane. Several types of ML classifiers are proposed and their performance is tested and compared for two real DWDM network topologies. The results obtained are promising and motivate further research.     

视觉模式识别网络及光电实现

在形态学网络及改进的Ｈａｍｍｉｎｇ网络基础上，提出视觉模式识别网络及训练算法，形态学网络作为特征提取网络，具有相对图像平移和尺度不变的特性，改进的Ｈａｍｍｉｎｇ网络加速完成特征矢量的分类操作。经过学习的视觉模式识别网络，可完成图像特征的提取，实现相对于图像平移和尺度不变的模式识别，在此基础上，建立了光电视觉模式识别体系，从而实现实时模式识别。     

基于小波神经网络的振动速度传感器幅频特性补偿研究

为了实现超低频振动速度测量, 提出补偿其幅频特性的小波神经网络方法.该方法以振动速度传感器动态实验数据为基础, 通过小波神经网络训练来确定传感器幅频特性补偿网络.介绍振动速度传感器幅频特性补偿原理, 分析网络的拓扑结构, 给出网络参数训练和初始化方法.采用引入动量项的最速下降法训练网络权值、尺度因子和平移因子, 将小波网络参数的初始化与小波类型、小波时频参数和学习样本等联系起来.结果表明, 采用小波神经网络进行振动速度传感器幅频特性补偿具有良好的鲁棒性,并能实现在线补偿,网络训练的速度和精度优于同等规模的BP网络,在测试领域有重要的实用价值. 关键词： 振动速度传感器 小波神经网络 幅频特性 补偿     

HL-2A tokamak disruption forecasting based on an artificial neural network

Artificial neural networks are trained to forecast the plasma disruption in HL-2A tokamak. Optimized network architecture is obtained. Saliency analysis is made to assess the relative importance of different diagnostic signals as network input. The trained networks can successfully detect the disruptive pulses of HL-2A tokamak. The results obtained show the possibility of developing a neural network predictor that intervenes well in advance for avoiding plasma disruption or mitigating its effects.     

Dynamic domain networks

A model for a dynamic network consisting of changing local interactions is presented in this work. While the network maintains solely local connections, certain properties known only to Small World Networks may be extracted due to the dynamic nature of the model. At each time step the individuals are grouped into clusters creating neighborhoods or domains of fully connected agents. The boundaries of these domains change in time, corresponding to a situation where the links between individuals are dynamic only throughout the history of the network. A question that we pose is whether our model, which maintains a local structure such that diffusion calculations are possible, might lead to analytic or conceptual advances for the much more complicated case of diffusion on a static disordered network that exhibits the same macroscopic properties as our dynamic ordered network. To answer this, we compare certain properties which characterize the dynamic domain network to those of a Small World Network, and then analyze the diffusion coefficients for three possible domain mutations. We close with a comparison and confirmation of previous epidemiological work carried out on networks.     

Chaos synchronization of a chain network based on a sliding mode control

A sliding mode control approach is proposed to implement the synchronization of the chain tree network. The doublescroll circuit chaos systems are treated as nodes and the network is constructed with the state variable coupling. By selecting a switching sliding surface, the chaos synchronization of the network is achieved with one control input only. The stability analysis and the numerical simulations demonstrate that the complete synchronization in a chain network can be realized for all nodes.     

Upstream access and local customer networking in passive optical networks using a single wavelength-seeded reflective semiconductor optical amplifier

A scheme for upstream transmission and local area network emulation in passive optical networks using a single reflective semiconductor optical amplifier placed at the customer premises is proposed and experimentally demonstrated. In this scheme, two optical carriers are delivered to the optical network units from the central office for the transmission of upstream and local area network signals, respectively.     

单向耦合神经元网络中螺旋波的自发形成机制

构造一个具有单向耦合的二维神经元网络，引入信息传输熵来描述定向信息传输，采用Hindmarsh-Rose神经元模型研究网络中螺旋波等有序波自发产生的机制.数值模拟表明：适当选取耦合的强度和单向耦合的距离，网络可自发出现螺旋波、行波、靶波和平面波.各种有序波的产生与网络中出现信息间歇定向传输有关，网络出现单或多螺旋波时发生熵共振现象.噪声、抑制性耦合和排斥性耦合诱发螺旋波时网络中也存在信息间歇定向传输.首次发现自维持长平面波，其存在是由于网络存在持续的强信息定向传输.     

面向LOFAR应用的160Gbit/s OTDM 试验平台

报告了一个用于低频射频天线网络LOFAR的160 Gbit/s 演示平台.文章介绍了LOFAR网络结构以及用于LOFAR长臂的OTDM/WDM系统结构，回顾并探讨了用于实现160 Gbit/s系统的关键技术，并介绍了实验室中实现该160 Gbit/s OTDM/WDM演示平台所采用的技术方案。出于经济性考虑，所有的关键系统功能都采用自己搭建方案.