多重边融合复杂动态网络的自适应同步

基于网络拆分的思想对多重边融合复杂动态网络局部和全局的自适应同步进行了研究.通过给出严格的数学定义及假设,运用Lyapunov稳定理论得出了网络局部和全局的同步准则,给出了更为简单的网络同步的控制器.最后以Lorenz 系统为例进行数值仿真,验证了结论的正确性和有效性. 关键词： 多重边融合复杂动态网络 自适应同步 网络拆分 时滞     

北京谱仪III上利用神经网络方法进行粒子鉴别的研究

本文描述了一种多层感知器的神经网络系统在BESIII粒子鉴别技术中的应用。网络按照子探测器分别进行训练, 输出结果可以作为后续网络的输入或者可以为似然函数方法构建概率密度函数。蒙特卡罗模拟样本的检验结果表明, 利用神经网络方法可以在BESIII上获得较好的粒子鉴别效果。     

多光谱成像技术诊断植物病虫害的人工神经网络模型

为了实现可靠的植物病虫害诊断,提出把人工神经网络和多光谱成像技术结合的方法,并将该方法用于常见的三种黄瓜病害的识别研究。在此基础上,实验采用窄带多光谱成像技术获取患病黄瓜叶面的14个可见光通道和近红外通道、全色通道的多光谱图像。利用BP网络对病斑样本的光谱信息进行学习分类。和14通道训练结果比较,增加850nm的近红外通道和全色通道,使网络的训练时间缩短、预测能力提高。实验结果表明,这种方法对植物进行快速、准确和非破坏性诊断提供可靠的技术支持。     

Synchronization of stochastically hybrid coupled neural networks with coupling discrete and distributed time-varying delays

A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed, which is composed of constant coupling, coupling discrete time-varying delay and coupling distributed timevarying delay. All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion, which reflects a more realistic dynamical behaviour of coupled systems in practice. Based on a simple adaptive feedback controller and stochastic stability theory, several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays. Finally, numerical simulations illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.     

Performance analysis of an integrated scheme in optical burst switching high-speed networks

A new integrated scheme based on resource-reservation and adaptive network flow routing to alleviate contention in optical burst switching networks is proposed. The objective of the proposed scheme is to reduce the overall burst loss in the network and at the same time to avoid the packet out-of-sequence arrival problem. Simulations are carried out to assess the feasibility of the proposed scheme. Its performance is compared with that of contention resolution schemes based on conventional routing. Through extensive simulations, it is shown that the proposed scheme not only provides significantly better burst loss performance than the basic equal proportion and hop-length based traffic routing algorithms, but also is void of any packet re-orderings.     

Synchronization of different chaotic systems via active radial basis functions sliding mode controller

This paper presents a new method to synchronize different chaotic systems with disturbances via an active radial basis function （RBF） sliding controller. This method incorporates the advantages of active control, neural network and sliding mode control. The main part of the controller is given based on the output of the RBF neural networks and the weights of these single layer networks are tuned on-line based on the sliding mode reaching law. Only several radial basis functions are required for this controller which takes the sliding mode variable as the only input. The proposed controller can make the synchronization error converge to zero quickly and can overcome external disturbances. Analysis of the stability for the controller is carried out based on the Lyapunov stability theorem. Finally, five examples are given to illustrate the robustness and effectiveness of the proposed synchronization control strategy.     

非线性函数耦合的Chen吸引子网络的混沌同步

利用非对称非线性函数耦合混沌同步方法,讨论了Chen吸引子的混沌同步问题,数值模拟分析初始值和耦合强度因子的选择对于实现混沌同步的影响. 将非对称非线性函数耦合同步方法进一步推广发展到完全连接网络和由星形子网络构成的复杂大网络混沌同步的研究中. 提供了确定网络中神经元之间混沌同步状态稳定性的误差发展方程,并讨论各个耦合强度因子对网络同步稳定性过程的影响,给出了相应的稳定性范围. 通过数值模拟证明利用非线性函数作为耦合函数,实现完全连接网络、星形子网络构成大网络的混沌同步是有效的. 可以预测在网络的混沌同步 关键词： 非线性耦合函数 Chen吸引子 混沌同步 网络     

All optical switching in semiconductor microresonators based on pattern selection

We present here a method for selecting optical patterns in a passive semiconductor microresonator, by using a spatial perturbation. A pattern is spontaneously generated in the system, and a switching beam causes this pattern to rotate even if the power in the switching beam is much lower than the power in the pattern. Thus, an all optical switch is realized, that operates at low light levels.     

基于人工神经网络的淫羊藿红外光谱的研究

对于不同产地和不同栽培条件的药材, 其药效的不同是由于其所含化学成分和各成分含量的比例不同所造成的, 这种差异将造成红外图谱的差异。但这些差异非常细微,单纯地从谱图去区分其特征是非常困难的。文章利用傅里叶变换红外光谱,测定了42种来自吉林3个不同产地的淫羊藿样品的红外光谱,并对光谱数据进行了相应的预处理。为了提高神经网络的训练速度,在利用人工神经网络建立模型之前,通过小波变换的方法对光谱变量进行了压缩。同时对建立的模型的相关参数进行了详细的讨论。实验表明,建立的模型能够正确地对42个淫羊藿样品进行产地鉴别,同时避免了传统光谱分析对药材的分离和提取,从而为中药质量的科学控制和现代化管理提供了可靠的依据。     

Pair correlations in scale-free networks

Correlation between nodes is found to be a common and important property in many complex networks. Here we investigate degree correlations of the Barabasi－Albert (BA) scale-free model with both analytical results and simulations, and find two neighbouring regions, a disassortative one for low degrees and a neutral one for high degrees. The average degree of the neighbours of a randomly picked node is expected to diverge in the limit of infinite network size. As a generalization of the concept of correlation, we also study the correlations of other scalar properties, including age and clustering coefficient. Finally we propose a correlation measurement in bipartite networks.